Coding method, decoding method, encoder, and decoder

ABSTRACT

An encoder which codes a moving picture includes: a processor; and a memory, wherein the processor, using the memory: subtracts a prediction image of an image included in the moving picture from the image so as to derive a prediction error; sequentially selects a plurality of transform basis candidates; derives an evaluation value of a transform basis candidate selected; compares the evaluation value with a threshold value; based on a result of the comparison, skips selection of one or more transform basis candidates that have not been selected; determines the transform basis from one or more transform basis candidates selected; performs the transform of the prediction error, using the transform basis; quantizes a result of the transform; and codes a result of the quantization as data of the image.

FIELD

The present disclosure relates to an encoder, etc., which codes a movingpicture.

BACKGROUND

As a standard for coding a moving picture, there has conventionally beenH.265 that is also referred to as high efficiency video coding (HEVC).

CITATION LIST Non Patent Literature

[NPL 1] H.265 (ISO/IEC 23008-2 HEVC)/HEVC (High Efficiency Video Coding)

SUMMARY Technical Problem

However, it is not easy to appropriately determine a transform basis tobe used in coding, etc., of a moving picture while reducing increase inprocessing amount.

In view of this, non-limiting and exemplary embodiments provide anencoder, etc., capable of appropriately determining transform baseswhile reducing increase in processing amount.

Solution to Problem

An encoder according to an aspect of the present disclosure codes amoving picture, the encoder including: a processor; and a memory,wherein the processor, using the memory: subtracts a prediction image ofan image included in the moving picture from the image so as to derive aprediction error of the image; sequentially selects a plurality oftransform basis candidates for a transform basis to be used to performtransform of the prediction error; derives an evaluation value of atransform basis candidate selected out of the plurality of transformbasis candidates; compares the evaluation value with a threshold value;based on a result of the comparison, skips selection of one or moretransform basis candidates that have not been selected out of theplurality of transform basis candidates; determines the transform basisfrom one or more transform basis candidates selected out of theplurality of transform basis candidates; performs the transform of theprediction error, using the transform basis; quantizes a result of thetransform; and codes a result of the quantization as data of the image.

These general and specific aspects may be implemented using a system, adevice, a method, an integrated circuit, a computer program, or anon-transitory computer-readable recording medium such as a CD-ROM, orany combination of systems, devices, methods, integrated circuits,computer programs, or computer-readable recording media.

Further benefits and advantageous effects provided by the disclosedembodiments are known from the Specification and the drawings. Thesebenefits and advantageous effects may be provided by various embodimentsand/or each of the features in the Specification and the drawings, andall of these benefits and advantageous effects do not always need to beprovided.

Advantageous Effects

The encoder, etc., according to an aspect of the present disclosure iscapable of appropriately determining transform bases while reducingincrease in processing amount.

BRIEF DESCRIPTION OF DRAWINGS

These and other objects, advantages and features of the disclosure willbecome apparent from the following description thereof taken inconjunction with the accompanying drawings that illustrate a specificembodiment of the present disclosure.

FIG. 1 is a block diagram illustrating a functional configuration of theencoding device according to Embodiment 1.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1.

FIG. 3 is a chart indicating transform basis functions for eachtransform type.

FIG. 4A illustrates one example of a filter shape used in ALF.

FIG. 4B illustrates another example of a filter shape used in ALF.

FIG. 4C illustrates another example of a filter shape used in ALF.

FIG. 5A illustrates 67 intra prediction modes used in intra prediction.

FIG. 5B is a flow chart for illustrating an outline of a predictionimage correction process performed via OBMC processing.

FIG. 5C is a conceptual diagram for illustrating an outline of aprediction image correction process performed via OBMC processing.

FIG. 5D illustrates one example of FRUC.

FIG. 6 is for illustrating pattern matching (bilateral matching) betweentwo blocks along a motion trajectory.

FIG. 7 is for illustrating pattern matching (template matching) betweena template in the current picture and a block in a reference picture.

FIG. 8 is for illustrating a model assuming uniform linear motion.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks.

FIG. 9B is for illustrating an outline of a process for deriving amotion vector via merge mode.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

FIG. 10 is a block diagram illustrating a functional configuration ofthe decoding device according to Embodiment 1.

FIG. 11 is a flowchart indicating a first specific example relating toprocessing for determining transform bases.

FIG. 12 is a flowchart indicating a second specific example relating toprocessing for determining transform bases.

FIG. 13 is a flowchart indicating a third specific example relating toprocessing for determining transform bases.

FIG. 14 is a flowchart indicating a fourth specific example relating toprocessing for determining transform bases.

FIG. 15 is a flowchart indicating a fifth specific example relating toprocessing for determining transform bases.

FIG. 16 is a block diagram indicating an implementation example of anencoder according to Embodiment 1.

FIG. 17 is a block diagram indicating an implementation example of adecoder according to Embodiment 1.

FIG. 18 illustrates an overall configuration of a content providingsystem for implementing a content distribution service.

FIG. 19 illustrates one example of encoding structure in scalableencoding.

FIG. 20 illustrates one example of encoding structure in scalableencoding.

FIG. 21 illustrates an example of a display screen of a web page.

FIG. 22 illustrates an example of a display screen of a web page.

FIG. 23 illustrates one example of a smartphone.

FIG. 24 is a block diagram illustrating a configuration example of asmartphone.

DESCRIPTION OF EMBODIMENTS

(Underlying Knowledge Forming Basis of the Present Disclosure)

For example, an encoder derives a prediction error by subtracting aprediction image from an image included in a moving picture when codingthe moving picture. The encoder performs frequency transform andquantization on the prediction error, and codes the result as data ofthe image.

In a natural image, the amount of frequency components is comparativelysmall. Accordingly, frequency transform centralizes information at thelow frequency side, which enables efficient coding. In addition,quantization removes the comparatively small amount of high frequencycomponents, reducing the amount of information. The high frequencycomponents less affect image quality, and thus the harmful effect ofimage quality deterioration is small.

For example, since the amount of high frequency components iscomparatively small, frequency transform and quantization sequentiallygenerates coefficients each having a value of 0 in the high frequencyregion. Here, the coefficients each having a value of 0 is referred toas a zero coefficient, and coefficients each having a value other than 0is referred to as a non-zero coefficient. The encoder is capable ofreducing the coding amount of zero coefficients generated sequentially.Accordingly, the encoder is capable of reducing the total coding amountby performing frequency transform and quantization.

In addition, the frequency transform is performed using a transformbasis. For example, the encoder determines a transform basis out of aplurality of transform basis candidates, and performs frequencytransform using the determined transform basis.

In addition, the decoder performs an operation corresponding to theoperation performed by the encoder. More specifically, the decoderdecodes data of an image. Subsequently, the decoder performs inversequantization and inverse frequency transform on the data of the image.Subsequently, the decoder derives the image by adding, as a predictionerror, the result of the inverse quantization and inverse frequencytransform to a prediction image.

In addition, the inverse frequency transform is also performed using atransform basis. For example, the decoder determines a transform basiscorresponding to the transform basis used in the transform out of theplurality of transform basis candidates, and performs inverse frequencytransform using the determined transform basis.

In addition, the encoder may perform secondary transform so that alarger number of zero coefficients are generated sequentially, after thefrequency transform and before the quantization. In this case, thefrequency transform is also represented as primary transform. Theprimary transform is not limited to frequency transform, and may beanother orthogonal transform, or the like. The secondary transform isbasically an orthogonal transform.

For example, the encoder determines a primary transform basis out of aplurality of primary transform basis candidates, determines a secondarytransform basis out of a plurality of secondary transform basiscandidates, performs primary transform on a prediction error using theprimary transform basis, and performs secondary transform on the resultof the primary transform using the secondary transform basis. In thiscase, the decoder performs inverse secondary transform on the result ofthe inverse quantization using the inverse secondary transform basiscorresponding to the secondary transform basis, and performs inverseprimary transform on the result of the inverse secondary transform usingthe inverse primary transform basis corresponding to the primarytransform basis.

The secondary transform performed in addition to the primary transformmay further reduce the coding amount.

However, it is not easy to appropriately determine a transform basiswhile reducing increase in the processing amount. For example, when theencoder derives an evaluation value for each of the plurality oftransform basis candidates and determines the transform basis candidatethat provides the highest evaluation value as a transform basis, theencoder is capable of appropriately determining the transform basis, butrequires a large processing amount to derive the evaluation value.

In view of this, an encoder which codes a moving picture according to anaspect of the present disclosure includes: a processor; and a memory,wherein the processor, using the memory: subtracts a prediction image ofan image included in the moving picture from the image so as to derive aprediction error of the image; sequentially selects a plurality oftransform basis candidates for a transform basis to be used to performtransform of the prediction error; derives an evaluation value of atransform basis candidate selected out of the plurality of transformbasis candidates; compares the evaluation value with a threshold value;based on a result of the comparison, skips selection of one or moretransform basis candidates that have not been selected out of theplurality of transform basis candidates; determines the transform basisfrom one or more transform basis candidates selected out of theplurality of transform basis candidates; performs the transform of theprediction error, using the transform basis; quantizes a result of thetransform; and codes a result of the quantization as data of the image.

In this way, the encoder is capable of skipping evaluation of anothertransform basis candidate, based on the result of the comparison betweenthe evaluation value of the transform basis candidate evaluated and thethreshold value. Subsequently, the encoder is capable of determining thetransform basis from the one or more transform basis candidatesevaluated. Accordingly, the encoder is capable of appropriatelydetermining the transform basis while reducing increase in theprocessing amount.

In addition, for example, the transform includes primary transform andsecondary transform, the transform basis is a combination of a primarytransform basis that is a transform basis for use in the primarytransform and a secondary transform basis that is a transform basis foruse in the secondary transform, and each of the plurality of transformbasis candidates is a combination of one of a plurality of primarytransform basis candidates for the primary transform basis and one of aplurality of secondary transform basis candidates for the secondarytransform basis.

In this way, the encoder is capable of appropriately determining theprimary transform basis and the secondary transform basis out of theplurality of primary transform basis candidates and the plurality ofsecondary transform basis candidates.

In addition, for example, the processor: sequentially selects theplurality of transform basis candidates by sequentially selecting theplurality of primary transform basis candidates and sequentiallyselecting the plurality of secondary transform basis candidates; andbased on the result of the comparison, skips the selection of the one ormore transform basis candidates that have not been selected out of theplurality of transform basis candidates by ending the sequentialselection of the plurality of primary transform basis candidates andending the sequential selection of the plurality of secondary transformbasis candidates.

In this way, the encoder is capable of ending both the sequentialselection of the plurality of primary transform basis candidates and thesequential selection of the plurality of secondary transform basiscandidates, while reducing increase in the processing amount.

In addition, for example, the processor: sequentially selects theplurality of transform basis candidates by sequentially selecting theplurality of primary transform basis candidates and sequentiallyselecting the plurality of secondary transform basis candidates; andbased on the result of the comparison, skips the selection of the one ormore transform basis candidates that have not been selected out of theplurality of transform basis candidates by skipping one of selection ofone or more primary transform basis candidates that have not beenselected out of the plurality of primary transform basis candidates andselection of one or more secondary transform basis candidates that havenot been selected out of the plurality of secondary transform basiscandidates.

In this way, the encoder is capable of skipping the selection of the oneor more of the plurality of primary transform basis candidates and theselection of the one or more of the plurality of secondary transformbasis candidates, while reducing increase in the processing amount.

In addition, for example, when the result of the comparison shows thatthe evaluation value is better than the threshold value, the processorskips the selection of the one or more transform basis candidates thathave not been selected out of the plurality of transform basiscandidates.

In this way, the encoder is capable of skipping evaluation of the othertransform basis candidate when the evaluation value is better than thethreshold value. Subsequently, the encoder is capable of determining thetransform basis from the one or more transform basis candidatesevaluated. Accordingly, the encoder is capable of appropriatelydetermining the transform basis while reducing increase in theprocessing amount.

In addition, for example, the processor determines the threshold valueusing an evaluation value of another transform basis candidate selectedbefore the transform basis candidate selected.

In this way, the encoder is capable of appropriately determining thetransform basis, using the threshold value determined relative to theevaluation value of the other transform basis candidate evaluated.

In addition, for example, the processor determines the threshold valueusing a parameter to be coded when coding the moving picture.

In this way, the encoder is capable of appropriately determining thetransform basis, using the threshold value determined by thecoding-related parameter.

In addition, for example, when the transform basis candidate selected isa predetermined transform basis candidate, the processor skips theselection of the one or more transform basis candidates that have notbeen selected out of the plurality of transform basis candidates, basedon the result of the comparison.

In this way, regarding the predetermined transform basis candidateevaluated, the encoder is capable of skipping evaluation of the othertransform basis candidate, based on the result of the comparison betweenthe evaluation value and the threshold value.

In addition, for example, when a size of the transform is apredetermined size, the processor skips the selection of the one or moretransform basis candidates that have not been selected out of theplurality of transform basis candidates, based on the result of thecomparison.

In this way, regarding the transform of the predetermined size, theencoder is capable of skipping evaluation of the other transform basiscandidate, based on the result of the comparison between the evaluationvalue and the threshold value.

In addition, for example, the processor codes information indicating thetransform basis that is determined based on the result of thecomparison.

In this way, the encoder is capable of notifying the informationindicating the transform basis determined appropriately.

In addition, for example, a decoder which decodes a moving pictureaccording to an aspect of the present disclosure includes: a processor;and a memory, wherein the processor, using the memory: decodes data ofan image included in the moving picture; decodes information indicatinga transform basis determined based on a result of comparison between anevaluation value of a transform basis candidate and a threshold value;performs inverse quantization of the data decoded; performs inversetransform of a result of the inverse quantization, using the transformbasis indicated by the information decoded; and derives the image byadding, as a prediction error of the image, a result of the inversetransform to a prediction image of the image.

In this way, the decoder is capable of obtaining the informationindicating the transform basis determined appropriately. Subsequently,the decoder is capable of performing the inverse transform using thetransform basis determined appropriately.

In addition, for example, an encoder for cording a moving pictureaccording to an aspect of the present disclosure includes: a processor;and a memory, wherein the processor, using the memory: subtracts aprediction image of an image included in the moving picture from theimage so as to derive a prediction error of the image; sequentiallyselects a plurality of transform basis candidates for a transform basisto be used to perform transform of the prediction error; derives anevaluation value of a transform basis candidate selected out of theplurality of transform basis candidates; compares the evaluation valuewith a threshold value; based on a result of the comparison, skipsselection of one or more transform basis candidates that have not beenselected out of the plurality of transform basis candidates; determinesthe transform basis from one or more transform basis candidates selectedout of the plurality of transform basis candidates; performs thetransform of the prediction error, using the transform basis; quantizesa result of the transform; and codes a result of the quantization asdata of the image.

In this way, it is possible to skip evaluation of the other transformbasis candidate, based on the result of the comparison between theevaluation value of the transform basis candidate evaluated and thethreshold value. Subsequently, the encoder is capable of determining thetransform basis from the one or more transform basis candidatesevaluated. Accordingly, the encoder is capable of appropriatelydetermining the transform basis while reducing increase in theprocessing amount.

In addition, for example, a decoding method for decoding a movingpicture according to an aspect of the present disclosure includes:decoding data of an image included in the moving picture; decodinginformation indicating a transform basis determined based on a result ofcomparison between an evaluation value of a transform basis candidateand a threshold value; performing inverse quantization of the datadecoded; performing inverse transform of a result of the inversequantization, using the transform basis indicated by the informationdecoded; and deriving the image by adding, as a prediction error of theimage, a result of the inverse transform to a prediction image of theimage.

In this way, it is possible to obtain the information indicating thetransform basis determined appropriately. Subsequently, it is possibleto perform inverse transform using the transform basis determinedappropriately.

Furthermore, these general and specific aspects may be implemented usinga system, a device, a method, an integrated circuit, a computer program,or a non-transitory computer-readable recording medium such as a CD-ROM,or any combination of systems, devices, methods, integrated circuits,computer programs, or computer-readable recording media.

Hereinafter, embodiments will be described with reference to thedrawings.

Note that the embodiments described below each show a general orspecific example. The numerical values, shapes, materials, components,the arrangement and connection of the components, steps, order of thesteps, etc., indicated in the following embodiments are mere examples,and therefore are not intended to limit the scope of the claims.Therefore, among the components in the following embodiments, those notrecited in any of the independent claims defining the broadest inventiveconcepts are described as optional components.

Embodiment 1

First, an outline of Embodiment 1 will be presented. Embodiment 1 is oneexample of an encoding device and a decoding device to which theprocesses and/or configurations presented in subsequent description ofaspects of the present disclosure are applicable. Note that Embodiment 1is merely one example of an encoding device and a decoding device towhich the processes and/or configurations presented in the descriptionof aspects of the present disclosure are applicable. The processesand/or configurations presented in the description of aspects of thepresent disclosure can also be implemented in an encoding device and adecoding device different from those according to Embodiment 1.

When the processes and/or configurations presented in the description ofaspects of the present disclosure are applied to Embodiment 1, forexample, any of the following may be performed.

(1) regarding the encoding device or the decoding device according toEmbodiment 1, among components included in the encoding device or thedecoding device according to Embodiment 1, substituting a componentcorresponding to a component presented in the description of aspects ofthe present disclosure with a component presented in the description ofaspects of the present disclosure;

(2) regarding the encoding device or the decoding device according toEmbodiment 1, implementing discretionary changes to functions orimplemented processes performed by one or more components included inthe encoding device or the decoding device according to Embodiment 1,such as addition, substitution, or removal, etc., of such functions orimplemented processes, then substituting a component corresponding to acomponent presented in the description of aspects of the presentdisclosure with a component presented in the description of aspects ofthe present disclosure;

(3) regarding the method implemented by the encoding device or thedecoding device according to Embodiment 1, implementing discretionarychanges such as addition of processes and/or substitution, removal ofone or more of the processes included in the method, and thensubstituting a processes corresponding to a process presented in thedescription of aspects of the present disclosure with a processpresented in the description of aspects of the present disclosure;

(4) combining one or more components included in the encoding device orthe decoding device according to Embodiment 1 with a component presentedin the description of aspects of the present disclosure, a componentincluding one or more functions included in a component presented in thedescription of aspects of the present disclosure, or a component thatimplements one or more processes implemented by a component presented inthe description of aspects of the present disclosure;

(5) combining a component including one or more functions included inone or more components included in the encoding device or the decodingdevice according to Embodiment 1, or a component that implements one ormore processes implemented by one or more components included in theencoding device or the decoding device according to Embodiment 1 with acomponent presented in the description of aspects of the presentdisclosure, a component including one or more functions included in acomponent presented in the description of aspects of the presentdisclosure, or a component that implements one or more processesimplemented by a component presented in the description of aspects ofthe present disclosure;

(6) regarding the method implemented by the encoding device or thedecoding device according to Embodiment 1, among processes included inthe method, substituting a process corresponding to a process presentedin the description of aspects of the present disclosure with a processpresented in the description of aspects of the present disclosure; and

(7) combining one or more processes included in the method implementedby the encoding device or the decoding device according to Embodiment 1with a process presented in the description of aspects of the presentdisclosure.

Note that the implementation of the processes and/or configurationspresented in the description of aspects of the present disclosure is notlimited to the above examples. For example, the processes and/orconfigurations presented in the description of aspects of the presentdisclosure may be implemented in a device used for a purpose differentfrom the moving picture/picture encoding device or the movingpicture/picture decoding device disclosed in Embodiment 1. Moreover, theprocesses and/or configurations presented in the description of aspectsof the present disclosure may be independently implemented. Moreover,processes and/or configurations described in different aspects may becombined.

[Encoding Device Outline]

First, the encoding device according to Embodiment 1 will be outlined.FIG. 1 is a block diagram illustrating a functional configuration ofencoding device 100 according to Embodiment 1. Encoding device 100 is amoving picture/picture encoding device that encodes a movingpicture/picture block by block.

As illustrated in FIG. 1, encoding device 100 is a device that encodes apicture block by block, and includes splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, block memory 118, loop filter120, frame memory 122, intra predictor 124, inter predictor 126, andprediction controller 128.

Encoding device 100 is realized as, for example, a generic processor andmemory. In this case, when a software program stored in the memory isexecuted by the processor, the processor functions as splitter 102,subtractor 104, transformer 106, quantizer 108, entropy encoder 110,inverse quantizer 112, inverse transformer 114, adder 116, loop filter120, intra predictor 124, inter predictor 126, and prediction controller128. Alternatively, encoding device 100 may be realized as one or morededicated electronic circuits corresponding to splitter 102, subtractor104, transformer 106, quantizer 108, entropy encoder 110, inversequantizer 112, inverse transformer 114, adder 116, loop filter 120,intra predictor 124, inter predictor 126, and prediction controller 128.

Hereinafter, each component included in encoding device 100 will bedescribed.

[Splitter]

Splitter 102 splits each picture included in an input moving pictureinto blocks, and outputs each block to subtractor 104. For example,splitter 102 first splits a picture into blocks of a fixed size (forexample, 128×128). The fixed size block is also referred to as codingtree unit (CTU). Splitter 102 then splits each fixed size block intoblocks of variable sizes (for example, 64×64 or smaller), based onrecursive quadtree and/or binary tree block splitting. The variable sizeblock is also referred to as a coding unit (CU), a prediction unit (PU),or a transform unit (TU). Note that in this embodiment, there is no needto differentiate between CU, PU, and TU; all or some of the blocks in apicture may be processed per CU, PU, or TU.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1. In FIG. 2, the solid lines represent block boundaries ofblocks split by quadtree block splitting, and the dashed lines representblock boundaries of blocks split by binary tree block splitting.

Here, block 10 is a square 128×128 pixel block (128×128 block). This128×128 block 10 is first split into four square 64×64 blocks (quadtreeblock splitting).

The top left 64×64 block is further vertically split into two rectangle32×64 blocks, and the left 32×64 block is further vertically split intotwo rectangle 16×64 blocks (binary tree block splitting). As a result,the top left 64×64 block is split into two 16×64 blocks 11 and 12 andone 32×64 block 13.

The top right 64×64 block is horizontally split into two rectangle 64×32blocks 14 and 15 (binary tree block splitting).

The bottom left 64×64 block is first split into four square 32×32 blocks(quadtree block splitting). The top left block and the bottom rightblock among the four 32×32 blocks are further split. The top left 32×32block is vertically split into two rectangle 16×32 blocks, and the right16×32 block is further horizontally split into two 16×16 blocks (binarytree block splitting). The bottom right 32×32 block is horizontallysplit into two 32×16 blocks (binary tree block splitting). As a result,the bottom left 64×64 block is split into 16×32 block 16, two 16×16blocks 17 and 18, two 32×32 blocks 19 and 20, and two 32×16 blocks 21and 22.

The bottom right 64×64 block 23 is not split. As described above, inFIG. 2, block 10 is split into 13 variable size blocks 11 through 23based on recursive quadtree and binary tree block splitting. This typeof splitting is also referred to as quadtree plus binary tree (QTBT)splitting.

Note that in FIG. 2, one block is split into four or two blocks(quadtree or binary tree block splitting), but splitting is not limitedto this example. For example, one block may be split into three blocks(ternary block splitting). Splitting including such ternary blocksplitting is also referred to as multi-type tree (MBT) splitting.

[Subtractor]

Subtractor 104 subtracts a prediction signal (prediction sample) from anoriginal signal (original sample) per block split by splitter 102. Inother words, subtractor 104 calculates prediction errors (also referredto as residuals) of a block to be encoded (hereinafter referred to as acurrent block). Subtractor 104 then outputs the calculated predictionerrors to transformer 106.

The original signal is a signal input into encoding device 100, and is asignal representing an image for each picture included in a movingpicture (for example, a luma signal and two chroma signals).Hereinafter, a signal representing an image is also referred to as asample.

[Transformer]

Transformer 106 transforms spatial domain prediction errors intofrequency domain transform coefficients, and outputs the transformcoefficients to quantizer 108. More specifically, transformer 106applies, for example, a predefined discrete cosine transform (DCT) ordiscrete sine transform (DST) to spatial domain prediction errors.

Note that transformer 106 may adaptively select a transform type fromamong a plurality of transform types, and transform prediction errorsinto transform coefficients by using a transform basis functioncorresponding to the selected transform type. This sort of transform isalso referred to as explicit multiple core transform (EMT) or adaptivemultiple transform (AMT).

The transform types include, for example, DCT-II, DCT-V, DCT-VIII,DST-I, and DST-VII. FIG. 3 is a chart indicating transform basisfunctions for each transform type. In FIG. 3, N indicates the number ofinput pixels. For example, selection of a transform type from among theplurality of transform types may depend on the prediction type (intraprediction and inter prediction), and may depend on intra predictionmode.

Information indicating whether to apply such EMT or AMT (referred to as,for example, an AMT flag) and information indicating the selectedtransform type is signalled at the CU level. Note that the signaling ofsuch information need not be performed at the CU level, and may beperformed at another level (for example, at the sequence level, picturelevel, slice level, tile level, or CTU level).

Moreover, transformer 106 may apply a secondary transform to thetransform coefficients (transform result). Such a secondary transform isalso referred to as adaptive secondary transform (AST) or non-separablesecondary transform (NSST). For example, transformer 106 applies asecondary transform to each sub-block (for example, each 4×4 sub-block)included in the block of the transform coefficients corresponding to theintra prediction errors. Information indicating whether to apply NSSTand information related to the transform matrix used in NSST aresignalled at the CU level. Note that the signaling of such informationneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, or CTU level).

Here, a separable transform is a method in which a transform isperformed a plurality of times by separately performing a transform foreach direction according to the number of dimensions input. Anon-separable transform is a method of performing a collective transformin which two or more dimensions in a multidimensional input arecollectively regarded as a single dimension.

In one example of a non-separable transform, when the input is a 4×4block, the 4×4 block is regarded as a single array including 16components, and the transform applies a 16×16 transform matrix to thearray. Moreover, similar to above, after an input 4×4 block is regardedas a single array including 16 components, a transform that performs aplurality of Givens rotations on the array (i.e., a Hypercube-GivensTransform) is also one example of a non-separable transform.

[Quantizer]

Ouantizer 108 quantizes the transform coefficients output fromtransformer 106. More specifically, quantizer 108 scans, in apredetermined scanning order, the transform coefficients of the currentblock, and quantizes the scanned transform coefficients based onquantization parameters (QP) corresponding to the transformcoefficients. Quantizer 108 then outputs the quantized transformcoefficients (hereinafter referred to as quantized coefficients) of thecurrent block to entropy encoder 110 and inverse quantizer 112.

A predetermined order is an order for quantizing/inverse quantizingtransform coefficients. For example, a predetermined scanning order isdefined as ascending order of frequency (from low to high frequency) ordescending order of frequency (from high to low frequency).

A quantization parameter is a parameter defining a quantization stepsize (quantization width). For example, if the value of the quantizationparameter increases, the quantization step size also increases. In otherwords, if the value of the quantization parameter increases, thequantization error increases.

[Entropy Encoder]

Entropy encoder 110 generates an encoded signal (encoded bitstream) byvariable length encoding quantized coefficients, which are inputs fromquantizer 108. More specifically, entropy encoder 110, for example,binarizes quantized coefficients and arithmetic encodes the binarysignal.

[Inverse Quantizer]

Inverse quantizer 112 inverse quantizes quantized coefficients, whichare inputs from quantizer 108. More specifically, inverse quantizer 112inverse quantizes, in a predetermined scanning order, quantizedcoefficients of the current block. Inverse quantizer 112 then outputsthe inverse quantized transform coefficients of the current block toinverse transformer 114.

[Inverse Transformer]

Inverse transformer 114 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 112. More specifically, inverse transformer 114 restores theprediction errors of the current block by applying an inverse transformcorresponding to the transform applied by transformer 106 on thetransform coefficients. Inverse transformer 114 then outputs therestored prediction errors to adder 116.

Note that since information is lost in quantization, the restoredprediction errors do not match the prediction errors calculated bysubtractor 104. In other words, the restored prediction errors includequantization errors.

[Adder]

Adder 116 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 114, and prediction samples,which are inputs from prediction controller 128. Adder 116 then outputsthe reconstructed block to block memory 118 and loop filter 120. Areconstructed block is also referred to as a local decoded block.

[Block Memory]

Block memory 118 is storage for storing blocks in a picture to beencoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 118 storesreconstructed blocks output from adder 116.

[Loop Filter]

Loop filter 120 applies a loop filter to blocks reconstructed by adder116, and outputs the filtered reconstructed blocks to frame memory 122.A loop filter is a filter used in an encoding loop (in-loop filter), andincludes, for example, a deblocking filter (DF), a sample adaptiveoffset (SAO), and an adaptive loop filter (ALF).

In ALF, a least square error filter for removing compression artifactsis applied. For example, one filter from among a plurality of filters isselected for each 2×2 sub-block in the current block based on directionand activity of local gradients, and is applied.

More specifically, first, each sub-block (for example, each 2×2sub-block) is categorized into one out of a plurality of classes (forexample, 15 or 25 classes). The classification of the sub-block is basedon gradient directionality and activity. For example, classificationindex C is derived based on gradient directionality D (for example, 0 to2 or 0 to 4) and gradient activity A (for example, 0 to 4) (for example,C=5D+A). Then, based on classification index C, each sub-block iscategorized into one out of a plurality of classes (for example, 15 or25 classes).

For example, gradient directionality D is calculated by comparinggradients of a plurality of directions (for example, the horizontal,vertical, and two diagonal directions). Moreover, for example, gradientactivity A is calculated by summing gradients of a plurality ofdirections and quantizing the sum.

The filter to be used for each sub-block is determined from among theplurality of filters based on the result of such categorization.

The filter shape to be used in ALF is, for example, a circular symmetricfilter shape. FIG. 4A through FIG. 4C illustrate examples of filtershapes used in ALF. FIG. 4A illustrates a 5×5 diamond shape filter, FIG.4B illustrates a 7×7 diamond shape filter, and FIG. 4C illustrates a 9×9diamond shape filter. Information indicating the filter shape issignalled at the picture level. Note that the signaling of informationindicating the filter shape need not be performed at the picture level,and may be performed at another level (for example, at the sequencelevel, slice level, tile level, CTU level, or CU level).

The enabling or disabling of ALF is determined at the picture level orCU level. For example, for luma, the decision to apply ALF or not isdone at the CU level, and for chroma, the decision to apply ALF or notis done at the picture level. Information indicating whether ALF isenabled or disabled is signalled at the picture level or CU level. Notethat the signaling of information indicating whether ALF is enabled ordisabled need not be performed at the picture level or CU level, and maybe performed at another level (for example, at the sequence level, slicelevel, tile level, or CTU level).

The coefficients set for the plurality of selectable filters (forexample, 15 or 25 filters) is signalled at the picture level. Note thatthe signaling of the coefficients set need not be performed at thepicture level, and may be performed at another level (for example, atthe sequence level, slice level, tile level, CTU level, CU level, orsub-block level).

[Frame Memory]

Frame memory 122 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 122 stores reconstructed blocks filtered byloop filter 120.

[Intra Predictor]

Intra predictor 124 generates a prediction signal (intra predictionsignal) by intra predicting the current block with reference to a blockor blocks in the current picture and stored in block memory 118 (alsoreferred to as intra frame prediction). More specifically, intrapredictor 124 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 128.

For example, intra predictor 124 performs intra prediction by using onemode from among a plurality of predefined intra prediction modes. Theintra prediction modes include one or more non-directional predictionmodes and a plurality of directional prediction modes.

The one or more non-directional prediction modes include, for example,planar prediction mode and DC prediction mode defined in theH.265/high-efficiency video coding (HEVC) standard (see NPTL 1).

The plurality of directional prediction modes include, for example, the33 directional prediction modes defined in the H.265/HEVC standard. Notethat the plurality of directional prediction modes may further include32 directional prediction modes in addition to the 33 directionalprediction modes (for a total of 65 directional prediction modes). FIG.5A illustrates 67 intra prediction modes used in intra prediction (twonon-directional prediction modes and 65 directional prediction modes).The solid arrows represent the 33 directions defined in the H.265/HEVCstandard, and the dashed arrows represent the additional 32 directions.

Note that a luma block may be referenced in chroma block intraprediction. In other words, a chroma component of the current block maybe predicted based on a luma component of the current block. Such intraprediction is also referred to as cross-component linear model (CCLM)prediction. Such a chroma block intra prediction mode that references aluma block (referred to as, for example, CCLM mode) may be added as oneof the chroma block intra prediction modes.

Intra predictor 124 may correct post-intra-prediction pixel values basedon horizontal/vertical reference pixel gradients. Intra predictionaccompanied by this sort of correcting is also referred to as positiondependent intra prediction combination (PDPC). Information indicatingwhether to apply PDPC or not (referred to as, for example, a PDPC flag)is, for example, signalled at the CU level. Note that the signaling ofthis information need not be performed at the CU level, and may beperformed at another level (for example, on the sequence level, picturelevel, slice level, tile level, or CTU level).

[Inter Predictor]

Inter predictor 126 generates a prediction signal (inter predictionsignal) by inter predicting the current block with reference to a blockor blocks in a reference picture, which is different from the currentpicture and is stored in frame memory 122 (also referred to as interframe prediction). Inter prediction is performed per current block orper sub-block (for example, per 4×4 block) in the current block. Forexample, inter predictor 126 performs motion estimation in a referencepicture for the current block or sub-block. Inter predictor 126 thengenerates an inter prediction signal of the current block or sub-blockby motion compensation by using motion information (for example, amotion vector) obtained from motion estimation. Inter predictor 126 thenoutputs the generated inter prediction signal to prediction controller128.

The motion information used in motion compensation is signalled. Amotion vector predictor may be used for the signaling of the motionvector. In other words, the difference between the motion vector and themotion vector predictor may be signalled.

Note that the inter prediction signal may be generated using motioninformation for a neighboring block in addition to motion informationfor the current block obtained from motion estimation. Morespecifically, the inter prediction signal may be generated per sub-blockin the current block by calculating a weighted sum of a predictionsignal based on motion information obtained from motion estimation and aprediction signal based on motion information for a neighboring block.Such inter prediction (motion compensation) is also referred to asoverlapped block motion compensation (OBMC).

In such an OBMC mode, information indicating sub-block size for OBMC(referred to as, for example, OBMC block size) is signalled at thesequence level. Moreover, information indicating whether to apply theOBMC mode or not (referred to as, for example, an OBMC flag) issignalled at the CU level. Note that the signaling of such informationneed not be performed at the sequence level and CU level, and may beperformed at another level (for example, at the picture level, slicelevel, tile level, CTU level, or sub-block level).

Hereinafter, the OBMC mode will be described in further detail. FIG. 5Bis a flowchart and FIG. 5C is a conceptual diagram for illustrating anoutline of a prediction image correction process performed via OBMCprocessing.

First, a prediction image (Pred) is obtained through typical motioncompensation using a motion vector (MV) assigned to the current block.

Next, a prediction image (Pred_L) is obtained by applying a motionvector (MV_L) of the encoded neighboring left block to the currentblock, and a first pass of the correction of the prediction image ismade by superimposing the prediction image and Pred_L.

Similarly, a prediction image (Pred_U) is obtained by applying a motionvector (MV_U) of the encoded neighboring upper block to the currentblock, and a second pass of the correction of the prediction image ismade by superimposing the prediction image resulting from the first passand Pred_U. The result of the second pass is the final prediction image.

Note that the above example is of a two-pass correction method using theneighboring left and upper blocks, but the method may be a three-pass orhigher correction method that also uses the neighboring right and/orlower block.

Note that the region subject to superimposition may be the entire pixelregion of the block, and, alternatively, may be a partial block boundaryregion.

Note that here, the prediction image correction process is described asbeing based on a single reference picture, but the same applies when aprediction image is corrected based on a plurality of referencepictures. In such a case, after corrected prediction images resultingfrom performing correction based on each of the reference pictures areobtained, the obtained corrected prediction images are furthersuperimposed to obtain the final prediction image.

Note that the unit of the current block may be a prediction block and,alternatively, may be a sub-block obtained by further dividing theprediction block.

One example of a method for determining whether to implement OBMCprocessing is by using an obmc_flag, which is a signal that indicateswhether to implement OBMC processing. As one specific example, theencoding device determines whether the current block belongs to a regionincluding complicated motion. The encoding device sets the obmc_flag toa value of “1” when the block belongs to a region including complicatedmotion and implements OBMC processing when encoding, and sets theobmc_flag to a value of “0” when the block does not belong to a regionincluding complication motion and encodes without implementing OBMCprocessing. The decoding device switches between implementing OBMCprocessing or not by decoding the obmc_flag written in the stream andperforming the decoding in accordance with the flag value.

Note that the motion information may be derived on the decoding deviceside without being signalled. For example, a merge mode defined in theH.265/HEVC standard may be used. Moreover, for example, the motioninformation may be derived by performing motion estimation on thedecoding device side. In this case, motion estimation is performedwithout using the pixel values of the current block.

Here, a mode for performing motion estimation on the decoding deviceside will be described. A mode for performing motion estimation on thedecoding device side is also referred to as pattern matched motionvector derivation (PMMVD) mode or frame rate up-conversion (FRUC) mode.

One example of FRUC processing is illustrated in FIG. 5D. First, acandidate list (a candidate list may be a merge list) of candidates eachincluding a motion vector predictor is generated with reference tomotion vectors of encoded blocks that spatially or temporally neighborthe current block. Next, the best candidate MV is selected from among aplurality of candidate MVs registered in the candidate list. Forexample, evaluation values for the candidates included in the candidatelist are calculated and one candidate is selected based on thecalculated evaluation values.

Next, a motion vector for the current block is derived from the motionvector of the selected candidate. More specifically, for example, themotion vector for the current block is calculated as the motion vectorof the selected candidate (best candidate MV), as-is. Alternatively, themotion vector for the current block may be derived by pattern matchingperformed in the vicinity of a position in a reference picturecorresponding to the motion vector of the selected candidate. In otherwords, when the vicinity of the best candidate MV is searched via thesame method and an MV having a better evaluation value is found, thebest candidate MV may be updated to the MV having the better evaluationvalue, and the MV having the better evaluation value may be used as thefinal MV for the current block. Note that a configuration in which thisprocessing is not implemented is also acceptable.

The same processes may be performed in cases in which the processing isperformed in units of sub-blocks.

Note that an evaluation value is calculated by calculating thedifference in the reconstructed image by pattern matching performedbetween a region in a reference picture corresponding to a motion vectorand a predetermined region. Note that the evaluation value may becalculated by using some other information in addition to thedifference.

The pattern matching used is either first pattern matching or secondpattern matching. First pattern matching and second pattern matching arealso referred to as bilateral matching and template matching,respectively.

In the first pattern matching, pattern matching is performed between twoblocks along the motion trajectory of the current block in two differentreference pictures. Therefore, in the first pattern matching, a regionin another reference picture conforming to the motion trajectory of thecurrent block is used as the predetermined region for theabove-described calculation of the candidate evaluation value.

FIG. 6 is for illustrating one example of pattern matching (bilateralmatching) between two blocks along a motion trajectory. As illustratedin FIG. 6, in the first pattern matching, two motion vectors (MV0, MV1)are derived by finding the best match between two blocks along themotion trajectory of the current block (Cur block) in two differentreference pictures (Ref0, Ref1). More specifically, a difference between(i) a reconstructed image in a specified position in a first encodedreference picture (Rem) specified by a candidate MV and (ii) areconstructed picture in a specified position in a second encodedreference picture (Ref1) specified by a symmetrical MV scaled at adisplay time interval of the candidate MV may be derived, and theevaluation value for the current block may be calculated by using thederived difference. The candidate MV having the best evaluation valueamong the plurality of candidate MVs may be selected as the final MV.

Under the assumption of continuous motion trajectory, the motion vectors(MV0, MV1) pointing to the two reference blocks shall be proportional tothe temporal distances (TD0, TD1) between the current picture (Cur Pic)and the two reference pictures (Ref0, Ref1). For example, when thecurrent picture is temporally between the two reference pictures and thetemporal distance from the current picture to the two reference picturesis the same, the first pattern matching derives a mirror basedbi-directional motion vector.

In the second pattern matching, pattern matching is performed between atemplate in the current picture (blocks neighboring the current block inthe current picture (for example, the top and/or left neighboringblocks)) and a block in a reference picture. Therefore, in the secondpattern matching, a block neighboring the current block in the currentpicture is used as the predetermined region for the above-describedcalculation of the candidate evaluation value.

FIG. 7 is for illustrating one example of pattern matching (templatematching) between a template in the current picture and a block in areference picture. As illustrated in FIG. 7, in the second patternmatching, a motion vector of the current block is derived by searching areference picture (Ref0) to find the block that best matches neighboringblocks of the current block (Cur block) in the current picture (CurPic). More specifically, a difference between (i) a reconstructed imageof an encoded region that is both or one of the neighboring left andneighboring upper region and (ii) a reconstructed picture in the sameposition in an encoded reference picture (Ref0) specified by a candidateMV may be derived, and the evaluation value for the current block may becalculated by using the derived difference. The candidate MV having thebest evaluation value among the plurality of candidate MVs may beselected as the best candidate MV.

Information indicating whether to apply the FRUC mode or not (referredto as, for example, a FRUC flag) is signalled at the CU level. Moreover,when the FRUC mode is applied (for example, when the FRUC flag is set totrue), information indicating the pattern matching method (first patternmatching or second pattern matching) is signalled at the CU level. Notethat the signaling of such information need not be performed at the CUlevel, and may be performed at another level (for example, at thesequence level, picture level, slice level, tile level, CTU level, orsub-block level).

Here, a mode for deriving a motion vector based on a model assuminguniform linear motion will be described. This mode is also referred toas a bi-directional optical flow (BIO) mode.

FIG. 8 is for illustrating a model assuming uniform linear motion. InFIG. 8, (v_(x), v_(y)) denotes a velocity vector, and τ₀ and τ₁ denotetemporal distances between the current picture (Cur Pic) and tworeference pictures (Ref₀, Ref₁). (MVx₀, MVy₀) denotes a motion vectorcorresponding to reference picture Ref₀, and (MVx₁, MVy₁) denotes amotion vector corresponding to reference picture Ref1.

Here, under the assumption of uniform linear motion exhibited byvelocity vector (v_(x), v_(y)), (MVx₀, MVy₀) and (MVx₁, MVy₁) arerepresented as (v_(x)τ₀, v_(y)τ₀) and (−v_(x)τ₁, −v_(y)τ₁),respectively, and the following optical flow equation is given.

MATH. 1

∂I ^((k)) ∂t+v _(x) ∂I ^((k)) /∂x+v _(y) ∂I ^((k)) /∂y=0.   (1)

Here, I^((k)) denotes a luma value from reference picture k (k=0, 1)after motion compensation. This optical flow equation shows that the sumof (i) the time derivative of the luma value, (ii) the product of thehorizontal velocity and the horizontal component of the spatial gradientof a reference picture, and (iii) the product of the vertical velocityand the vertical component of the spatial gradient of a referencepicture is equal to zero. A motion vector of each block obtained from,for example, a merge list is corrected pixel by pixel based on acombination of the optical flow equation and Hermite interpolation.

Note that a motion vector may be derived on the decoding device sideusing a method other than deriving a motion vector based on a modelassuming uniform linear motion. For example, a motion vector may bederived for each sub-block based on motion vectors of neighboringblocks.

Here, a mode in which a motion vector is derived for each sub-blockbased on motion vectors of neighboring blocks will be described. Thismode is also referred to as affine motion compensation prediction mode.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks. In FIG. 9A, the currentblock includes 16 4×4 sub-blocks. Here, motion vector v₀ of the top leftcorner control point in the current block is derived based on motionvectors of neighboring sub-blocks, and motion vector v₁ of the top rightcorner control point in the current block is derived based on motionvectors of neighboring blocks. Then, using the two motion vectors v₀ andv₁, the motion vector (v_(x), v_(y)) of each sub-block in the currentblock is derived using Equation 2 below.

$\begin{matrix}{{MATH}.\mspace{14mu} 2} & \; \\\left\{ \begin{matrix}{v_{x} = {{\frac{\left( {v_{1x} - v_{0x}} \right)}{w}x} - {\frac{\left( {v_{1y} - v_{0_{y}}} \right)}{w}y} + v_{0x}}} \\{v_{y} = {{\frac{\left( {v_{1y} - v_{0y}} \right)}{w}x} + {\frac{\left( {v_{1x} - v_{0x}} \right)}{w}y} + v_{0y}}}\end{matrix} \right. & (2)\end{matrix}$

Here, x and y are the horizontal and vertical positions of thesub-block, respectively, and w is a predetermined weighted coefficient.

Such an affine motion compensation prediction mode may include a numberof modes of different methods of deriving the motion vectors of the topleft and top right corner control points. Information indicating such anaffine motion compensation prediction mode (referred to as, for example,an affine flag) is signalled at the CU level. Note that the signaling ofinformation indicating the affine motion compensation prediction modeneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, CTU level, or sub-block level).

[Prediction Controller]

Prediction controller 128 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto subtractor 104 and adder 116.

Here, an example of deriving a motion vector via merge mode in a currentpicture will be given. FIG. 9B is for illustrating an outline of aprocess for deriving a motion vector via merge mode.

First, an MV predictor list in which candidate MV predictors areregistered is generated. Examples of candidate MV predictors include:spatially neighboring MV predictors, which are MVs of encoded blockspositioned in the spatial vicinity of the current block; a temporallyneighboring MV predictor, which is an MV of a block in an encodedreference picture that neighbors a block in the same location as thecurrent block; a combined MV predictor, which is an MV generated bycombining the MV values of the spatially neighboring MV predictor andthe temporally neighboring MV predictor; and a zero MV predictor, whichis an MV whose value is zero.

Next, the MV of the current block is determined by selecting one MVpredictor from among the plurality of MV predictors registered in the MVpredictor list.

Furthermore, in the variable-length encoding device, a merge_idx, whichis a signal indicating which MV predictor is selected, is written andencoded into the stream.

Note that the MV predictors registered in the MV predictor listillustrated in FIG. 9B constitute one example. The number of MVpredictors registered in the MV predictor list may be different from thenumber illustrated in FIG. 9B, the MV predictors registered in the MVpredictor list may omit one or more of the types of MV predictors givenin the example in FIG. 9B, and the MV predictors registered in the MVpredictor list may include one or more types of MV predictors inaddition to and different from the types given in the example in FIG.9B.

Note that the final MV may be determined by performing DMVR processing(to be described later) by using the MV of the current block derived viamerge mode.

Here, an example of determining an MV by using DMVR processing will begiven.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

First, the most appropriate MVP set for the current block is consideredto be the candidate MV, reference pixels are obtained from a firstreference picture, which is a picture processed in the L0 direction inaccordance with the candidate MV, and a second reference picture, whichis a picture processed in the L1 direction in accordance with thecandidate MV, and a template is generated by calculating the average ofthe reference pixels.

Next, using the template, the surrounding regions of the candidate MVsof the first and second reference pictures are searched, and the MV withthe lowest cost is determined to be the final MV. Note that the costvalue is calculated using, for example, the difference between eachpixel value in the template and each pixel value in the regionssearched, as well as the MV value.

Note that the outlines of the processes described here are fundamentallythe same in both the encoding device and the decoding device.

Note that processing other than the processing exactly as describedabove may be used, so long as the processing is capable of deriving thefinal MV by searching the surroundings of the candidate MV.

Here, an example of a mode that generates a prediction image by usingLIC processing will be given.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

First, an MV is extracted for obtaining, from an encoded referencepicture, a reference image corresponding to the current block.

Next, information indicating how the luminance value changed between thereference picture and the current picture is extracted and a luminancecorrection parameter is calculated by using the luminance pixel valuesfor the encoded left neighboring reference region and the encoded upperneighboring reference region, and the luminance pixel value in the samelocation in the reference picture specified by the MV.

The prediction image for the current block is generated by performing aluminance correction process by using the luminance correction parameteron the reference image in the reference picture specified by the MV.

Note that the shape of the surrounding reference region illustrated inFIG. 9D is just one example; the surrounding reference region may have adifferent shape.

Moreover, although a prediction image is generated from a singlereference picture in this example, in cases in which a prediction imageis generated from a plurality of reference pictures as well, theprediction image is generated after performing a luminance correctionprocess, via the same method, on the reference images obtained from thereference pictures.

One example of a method for determining whether to implement LICprocessing is by using an lic_flag, which is a signal that indicateswhether to implement LIC processing. As one specific example, theencoding device determines whether the current block belongs to a regionof luminance change. The encoding device sets the lic_flag to a value of“1” when the block belongs to a region of luminance change andimplements LIC processing when encoding, and sets the lic_flag to avalue of “0” when the block does not belong to a region of luminancechange and encodes without implementing LIC processing. The decodingdevice switches between implementing LIC processing or not by decodingthe lic_flag written in the stream and performing the decoding inaccordance with the flag value.

One example of a different method of determining whether to implementLIC processing is determining so in accordance with whether LICprocessing was determined to be implemented for a surrounding block. Inone specific example, when merge mode is used on the current block,whether LIC processing was applied in the encoding of the surroundingencoded block selected upon deriving the MV in the merge mode processingmay be determined, and whether to implement LIC processing or not can beswitched based on the result of the determination. Note that in thisexample, the same applies to the processing performed on the decodingdevice side.

[Decoding Device Outline]

Next, a decoding device capable of decoding an encoded signal (encodedbitstream) output from encoding device 100 will be described. FIG. 10 isa block diagram illustrating a functional configuration of decodingdevice 200 according to Embodiment 1. Decoding device 200 is a movingpicture/picture decoding device that decodes a moving picture/pictureblock by block.

As illustrated in FIG. 10, decoding device 200 includes entropy decoder202, inverse quantizer 204, inverse transformer 206, adder 208, blockmemory 210, loop filter 212, frame memory 214, intra predictor 216,inter predictor 218, and prediction controller 220.

Decoding device 200 is realized as, for example, a generic processor andmemory. In this case, when a software program stored in the memory isexecuted by the processor, the processor functions as entropy decoder202, inverse quantizer 204, inverse transformer 206, adder 208, loopfilter 212, intra predictor 216, inter predictor 218, and predictioncontroller 220. Alternatively, decoding device 200 may be realized asone or more dedicated electronic circuits corresponding to entropydecoder 202, inverse quantizer 204, inverse transformer 206, adder 208,loop filter 212, intra predictor 216, inter predictor 218, andprediction controller 220.

Hereinafter, each component included in decoding device 200 will bedescribed.

[Entropy Decoder]

Entropy decoder 202 entropy decodes an encoded bitstream. Morespecifically, for example, entropy decoder 202 arithmetic decodes anencoded bitstream into a binary signal. Entropy decoder 202 thendebinarizes the binary signal. With this, entropy decoder 202 outputsquantized coefficients of each block to inverse quantizer 204.

[Inverse Quantizer]

Inverse quantizer 204 inverse quantizes quantized coefficients of ablock to be decoded (hereinafter referred to as a current block), whichare inputs from entropy decoder 202. More specifically, inversequantizer 204 inverse quantizes quantized coefficients of the currentblock based on quantization parameters corresponding to the quantizedcoefficients. Inverse quantizer 204 then outputs the inverse quantizedcoefficients (i.e., transform coefficients) of the current block toinverse transformer 206.

[Inverse Transformer]

Inverse transformer 206 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 204.

For example, when information parsed from an encoded bitstream indicatesapplication of EMT or AMT (for example, when the AMT flag is set totrue), inverse transformer 206 inverse transforms the transformcoefficients of the current block based on information indicating theparsed transform type.

Moreover, for example, when information parsed from an encoded bitstreamindicates application of NSST, inverse transformer 206 applies asecondary inverse transform to the transform coefficients.

[Adder]

Adder 208 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 206, and prediction samples,which is an input from prediction controller 220. Adder 208 then outputsthe reconstructed block to block memory 210 and loop filter 212.

[Block Memory]

Block memory 210 is storage for storing blocks in a picture to bedecoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 210 storesreconstructed blocks output from adder 208.

[Loop Filter]

Loop filter 212 applies a loop filter to blocks reconstructed by adder208, and outputs the filtered reconstructed blocks to frame memory 214and, for example, a display device.

When information indicating the enabling or disabling of ALF parsed froman encoded bitstream indicates enabled, one filter from among aplurality of filters is selected based on direction and activity oflocal gradients, and the selected filter is applied to the reconstructedblock.

[Frame Memory]

Frame memory 214 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 214 stores reconstructed blocks filtered byloop filter 212.

[Intra Predictor]

Intra predictor 216 generates a prediction signal (intra predictionsignal) by intra prediction with reference to a block or blocks in thecurrent picture and stored in block memory 210. More specifically, intrapredictor 216 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 220.

Note that when an intra prediction mode in which a chroma block is intrapredicted from a luma block is selected, intra predictor 216 may predictthe chroma component of the current block based on the luma component ofthe current block.

Moreover, when information indicating the application of PDPC is parsedfrom an encoded bitstream, intra predictor 216 correctspost-intra-prediction pixel values based on horizontal/verticalreference pixel gradients.

[Inter Predictor]

Inter predictor 218 predicts the current block with reference to areference picture stored in frame memory 214. Inter prediction isperformed per current block or per sub-block (for example, per 4×4block) in the current block. For example, inter predictor 218 generatesan inter prediction signal of the current block or sub-block by motioncompensation by using motion information (for example, a motion vector)parsed from an encoded bitstream, and outputs the inter predictionsignal to prediction controller 220.

Note that when the information parsed from the encoded bitstreamindicates application of OBMC mode, inter predictor 218 generates theinter prediction signal using motion information for a neighboring blockin addition to motion information for the current block obtained frommotion estimation.

Moreover, when the information parsed from the encoded bitstreamindicates application of FRUC mode, inter predictor 218 derives motioninformation by performing motion estimation in accordance with thepattern matching method (bilateral matching or template matching) parsedfrom the encoded bitstream. Inter predictor 218 then performs motioncompensation using the derived motion information.

Moreover, when BIO mode is to be applied, inter predictor 218 derives amotion vector based on a model assuming uniform linear motion. Moreover,when the information parsed from the encoded bitstream indicates thataffine motion compensation prediction mode is to be applied, interpredictor 218 derives a motion vector of each sub-block based on motionvectors of neighboring blocks.

[Prediction Controller]

Prediction controller 220 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto adder 208.

[Transform Basis Determination Processing]

Next, a transform basis determination processing is described. Forexample, transformer 106 of encoder 100 performs transform of aprediction error, and performs re-transform of the result of thetransform. Subsequently, quantizer 108 of encoder 100 performsquantization of the result of the re-transform. The transform of theprediction error is also referred to as primary transform. The inversetransform of the result of the re-transform is also referred to assecondary transform. In other words, transformer 106 performs primarytransform of the prediction error, and performs secondary transform ofthe result of the primary transform.

More specifically, transformer 106 performs the primary transform of theprediction error using a primary transform basis. Subsequently,transformer 106 performs secondary transform of the result of theprimary transform using a secondary transform basis. The primarytransform basis is a transform basis of primary transform, and thesecondary transform basis is a transform basis of secondary transform.For example, the transform basis has a plurality of data patterns. Eachdata pattern may be referred to as a base. In this case, the transformbasis can be regarded as a basis set composed of a plurality of bases.

For example, transformer 106 performs primary transform of a predictionimage by deriving, from the prediction image, a component value of eachdata pattern of the primary transform basis. In other words, the resultof the primary transform corresponds to a plurality of component valuesderived from the prediction image, and corresponds to a plurality ofcomponent values corresponding to the data patterns of the primarytransform basis.

Subsequently, transformer 106 performs secondary transform of the resultof the primary transform by deriving a component value of each datapattern of the secondary transform basis from the result of the primarytransform. In other words, the result of the secondary transformcorresponds to a plurality of component values derived from the resultof the primary transform, and corresponds to a plurality of componentvalues corresponding to the data patterns of the secondary transformbasis.

In addition, decoder 200 performs an operation corresponding to theoperation performed by encoder 100. More specifically, inversetransformer 206 of decoder 200 performs inverse transform of the resultof the inverse quantization, using an inverse secondary transform basis.In addition, inverse transformer 206 performs inverse primary transformof the result of the inverse secondary transform, using an inverseprimary transform basis.

Here, the inverse primary transform is transform inverse to primarytransform. Inverse transformer 206 performs inverse primary transformusing the inverse primary transform basis, so as to derive data that hasnot been subjected to primary transform from the data already subjectedto the primary transform. The inverse primary transform basis is atransform basis that is of inverse primary transform and corresponds tothe primary transform basis.

More specifically, inverse transformer 206 may perform inverse primarytransform by performing processing according to a procedure opposite tothe primary transform, using the inverse primary transform basiscorresponding to the primary transform basis.

In addition, the inverse secondary transform is transform inverse to thesecondary transform. Inverse transformer 206 performs inverse secondarytransform using the inverse secondary transform basis, so as to derivedata that has not been subjected to primary transform from the dataalready subjected to the primary transform. The inverse secondarytransform basis is a transform basis that is of inverse secondarytransform and corresponds to the secondary transform basis.

More specifically, inverse transformer 206 may perform inverse secondarytransform by performing processing according to a procedure opposite tothe secondary transform, using the inverse secondary transform basiscorresponding to the secondary transform basis.

The result of the inverse quantization in inverse quantizer 206 ofdecoder 200 corresponds to the result of secondary transform intransformer 106 of encoder 100. In other words, the result of theinverse quantization corresponds to a plurality of component valuesderived from the result of the primary transform, and corresponds to aplurality of component values corresponding to the data patterns of thesecondary transform basis. For example, inverse transformer 206 derivesthe result of the primary transform by synthesizing these componentvalues using the inverse secondary transform basis when performing theinverse secondary transform of the result of the inverse quantization.

Accordingly, the result of the inverse secondary transform correspondsto the result of the primary transform in transformer 106 of encoder100. In other words, the result of the inverse secondary transformcorresponds to a plurality of component values derived from theprediction image, and corresponds to a plurality of component valuescorresponding to the data patterns of the primary transform basis. Forexample, inverse transformer 206 derives a prediction error bysynthesizing these component values using the inverse primary transformbasis when performing inverse primary transform of the result of theinverse secondary transform.

Transformer 106 according to an embodiment determines a combination of aprimary transform basis for use in primary transform and a secondarytransform basis for use in secondary transform. For example, transformer106 applies transform called EMT or AMT to primary transform, andperforms primary transform of a prediction error using a primarytransform basis determined adaptively. In addition, transformer 106applies transform called AST, NSST or the like to secondary transform,and performs re-transform of a transform coefficient generated by theprimary transform, using a secondary transform basis.

Transformer 106 determines a combination of a primary transform basisand a secondary transform basis in a plurality of primary transformbasis candidates and a plurality of secondary transform basiscandidates, and performs primary transform and secondary transform usingthe primary transform basis and the secondary transform basis that makeup the determined combination.

FIG. 11 is a flowchart indicating a first specific example relating toprocessing for determining transform bases. FIG. 11 illustrates anoperation for determining a combination of a primary transform basis anda secondary transform basis. For example, transformer 106 of encoder 100illustrated in FIG. 1 performs an operation illustrated in FIG. 11.

More specifically, in an example of FIG. 11, loop processing for each ofthe plurality of secondary transform basis candidates includes loopprocessing for each of the plurality of primary transform basiscandidates. Subsequently, in the loop processing, transformer 106selects a primary transform basis candidate as an evaluation targetprimary transform basis candidate (S101), and selects a secondarytransform basis candidate as an evaluation target secondary transformbasis candidate (S102). In other words, transformer 106 selects thecombination of a primary transform basis candidate and a secondarytransform basis candidate as the evaluation target transform basiscandidate.

Subsequently, transformer 106 derives a cost for the combination of theprimary transform basis candidate and the secondary transform basiscandidate (S103). This cost is, for example, a rate distortion cost(RD), and corresponds to an evaluation value. More specifically, thecost may be based on a coding amount and a difference between anoriginal image and a reconstructed image. Alternatively, the cost may bederived by a zero coefficient, a non-zero coefficient, or the like,based on the primary transform basis candidate and the secondarytransform basis candidate. In this embodiment, a less cost is better.

Subsequently, transformer 106 determines whether or not a cost is lessthan or equal to a threshold value (S105). Here, that a cost is lessthan or equal to a threshold value corresponds to that a combination ofa primary transform basis candidate and a secondary transform basiscandidate is appropriate. In addition, that a cost exceeds a thresholdvalue corresponds to that a combination of a primary transform basiscandidate and a secondary transform basis candidate is not appropriate.

When a cost is less than or equal to a threshold value (Yes in S105),transformer 106 ends the loop processing. In other words, in this case,transformer 106 ends the selection processing even when a combinationthat has not been selected and evaluated is left in the plurality ofprimary transform basis candidates and the plurality of secondarytransform basis candidates. Subsequently, transformer 106 determines theprimary transform basis candidate and the secondary transform basiscandidate making up the combination that yields the cost less than orequal to the threshold value as a final primary transform basis and afinal secondary transform basis.

When the cost exceeds the threshold value (No in S105), transformer 106continues the loop processing. Subsequently, transformer 106 repeatsprocessing until a combination that yields a cost less than or equal tothe threshold value is selected or no unselected combination is left.Transformer 106 may determine the primary transform basis candidate andthe secondary transform basis candidate making up the combination thatyields the least cost as a final primary transform basis and a finalsecondary transform basis when there is no cost that is less than orequal to the threshold value.

A large amount of processing is required to derive an evaluation valueof every combination of a primary transform basis candidate and asecondary transform basis candidate in the plurality of primarytransform basis candidates and the plurality of secondary transformbasis candidates. In view of this, transformer 106 is capable ofreducing increase in the amount of processing by ending the loopprocessing based on the result of comparison with respect to thethreshold value while selecting an appropriate combination of a primarytransform basis candidate and a secondary transform basis candidate.

Part of the processing included in the above-described operations maynot be performed. For example, one of the primary transform basiscandidate and the secondary transform basis candidate may not beselected, or a fixed primary transform basis candidate and a fixedsecondary transform basis candidate may be used.

In addition, the plurality of primary transform basis candidates mayinclude a primary transform basis candidate which is not transformed.When a primary transform basis candidate which is not transformed isdetermined as a primary transform basis, no primary transform isperformed. Alternatively, in this case, primary transform that does notchange data before and after the secondary transform may be performed.Likewise, the plurality of secondary transform basis candidates mayinclude a secondary transform basis candidate which is not transformed.When a secondary transform basis candidate which is not transformed isdetermined as a secondary transform basis, no secondary transform isperformed. Alternatively, in this case, secondary transform that doesnot change data before and after the secondary transform may beperformed.

FIG. 12 is a flowchart indicating a second specific example relating toa process for determining transform bases. FIG. 12 illustrates anoperation for determining a combination of a primary transform basis anda secondary transform basis. For example, transformer 106 of encoder 100illustrated in FIG. 1 performs the operation illustrated in FIG. 12.

More specifically, in an example of FIG. 12 as in the example of FIG.11, loop processing for each of the plurality of secondary transformbasis candidates includes loop processing for each of the plurality ofprimary transform basis candidates. Subsequently, in the loopprocessing, transformer 106 selects a primary transform basis candidateas an evaluation target primary transform basis candidate (S101), andselects a secondary transform basis candidate as an evaluation targetsecondary transform basis candidate (S102). In other words, transformer106 selects the combination of a primary transform basis candidate and asecondary transform basis candidate as the evaluation target transformbasis candidate.

In addition, as in the example of FIG. 11, transformer 106 derives acost for the combination of the primary transform basis candidate andthe secondary transform basis candidate (S103). Subsequently,transformer 106 determines whether or not a cost is less than or equalto a threshold value (S105).

In the example of FIG. 12, when the cost is less than or equal to thethreshold value (Yes in S105), transformer 106 ends the loop processingfor each of the plurality of primary transform basis candidates. Inother words, in this case, even when there is an unselected primarytransform basis candidate for a selected secondary transform basiscandidate, transformer 106 does not select the primary transform basiscandidate for the selected secondary transform basis candidate.

Subsequently, transformer 106 newly starts loop processing for each ofthe plurality of primary transform basis candidates in the loopprocessing for each of the plurality of secondary transform basiscandidates. Subsequently, transformer 106 selects a primary transformbasis candidate and a secondary transform basis candidate again (S101,S102). For example, the primary transform basis candidate to be selectedat this time is a primary transform basis candidate unselected for thesecondary transform basis candidate selected at this time, and thesecondary transform basis candidate to be selected at this time is anunselected secondary transform basis candidate.

When the cost exceeds the threshold value (No in S105), transformer 106continues loop processing for each of the plurality of primary transformbasis candidates. Subsequently, transformer 106 selects a primarytransform basis candidate and a secondary transform basis candidateagain (S101, S102). For example, the primary transform basis candidateto be selected at this time is a primary transform basis candidateunselected for the secondary transform basis candidate selected at thistime, and the secondary transform basis candidate to be selected at thistime is the secondary transform basis candidate selected just beforethis time.

Subsequently, transformer 106 performs the above-described processing(S101 to S103, and S105) by repeating loop processing for each of theplurality of primary transform basis candidates until the loopprocessing for each of the plurality of secondary transform basiscandidates ends. Subsequently, transformer 106 determines the primarytransform basis candidate and the secondary transform basis candidatemaking up the combination that yields the least cost out of thecombinations whose costs have been derived, as a final primary transformbasis and a final secondary transform basis.

In the example of FIG. 12, transformer 106 derives costs for a largernumber of combinations than in the example of FIG. 11. Accordingly,transformer 106 is capable of selecting a more appropriate combination.

For example, transformer 106 may select each of a plurality of primarytransform basis candidates in priority order. For example, transformer106 may select each of the plurality of primary transform basiscandidates in an ascending order of priority. In this way, transformer106 is capable of deriving a cost for a combination of a prioritytransform basis candidate having a high priority rank and each of theplurality of secondary transform basis candidates without skipping thecombination.

In addition, here, loop processing for each of the plurality ofsecondary transform basis candidates includes loop processing for eachof the plurality of primary transform basis candidates. However, theloop processing for each of the plurality of primary transform basiscandidates may include loop processing for each of the plurality ofsecondary transform basis candidates. Subsequently, when the cost isless than or equal to the threshold value, transformer 106 may end theloop processing for each of the plurality of secondary transform basiscandidates. In other words, the relationship between a primary transformbasis candidate and a secondary transform basis candidate may beinversed.

FIG. 13 is a flowchart indicating a third specific example relating toprocessing for determining transform bases. FIG. 13 illustrates anoperation for determining a combination of a primary transform basis anda secondary transform basis. For example, transformer 106 of encoder 100illustrated in FIG. 1 performs the operation illustrated in FIG. 13.

More specifically, in an example of FIG. 13 as in the example of FIG.11, loop processing for each of the plurality of secondary transformbasis candidates includes loop processing for each of the plurality ofprimary transform basis candidates. Subsequently, in the loopprocessing, transformer 106 selects a primary transform basis candidateas an evaluation target primary transform basis candidate (S101), andselects a secondary transform basis candidate as an evaluation targetsecondary transform basis candidate (S102). In other words, transformer106 selects the combination of a primary transform basis candidate and asecondary transform basis candidate as the evaluation target transformbasis candidate.

In addition, as in the example of FIG. 11, transformer 106 derives acost for the combination of the primary transform basis candidate andthe secondary transform basis candidate (S103). Subsequently, in theexample of FIG. 13, transformer 106 determines whether the cost is lessthan or equal to the threshold value and whether or not one of theprimary transform basis candidate and the secondary transform basiscandidate is a predetermined transform basis candidate (S106).

When the determination conditions are satisfied (Yes in S106),transformer 106 ends the loop processing. In other words, in this case,transformer 106 ends the selection processing even when a combinationthat has not been selected and evaluated is left in the plurality ofprimary transform basis candidates and the plurality of secondarytransform basis candidates. When the determination conditions are notsatisfied (No in S106), transformer 106 ends the loop processing. Here,transformer 106 repeats the processing until the determinationconditions are satisfied or no unselected combination is left.

Subsequently, transformer 106 determines the primary transform basiscandidate and the secondary transform basis candidate making up thecombination that yields the least cost out of the combinations whosecosts have been derived, as a final primary transform basis and a finalsecondary transform basis. Transformer 106 may determine the primarytransform basis candidate and the secondary transform basis candidatemaking up the combination that satisfies the determination conditions asa final primary transform basis and a final secondary transform basis.

In the example of FIG. 13, transformer 106 derives costs for a largernumber of combinations than in the example of FIG. 11. Accordingly,transformer 106 is capable of selecting a more appropriate combination.

In addition, whether or not the one of the primary transform basiscandidate and the secondary transform basis candidate is thepredetermined transform basis candidate may be whether or not theprimary transform basis candidate is the predetermined transform basiscandidate and whether or not the secondary transform basis candidate isthe predetermined transform basis candidate. For example, thepredetermined transform basis candidate may be a transform basiscorresponding to DCT 2. Transformer 106 may end loop processing onlywhen a cost is less than or equal to a threshold value and a firsttransform basis candidate is a transform basis corresponding to DCT 2.

In addition, a plurality of predetermined transform basis candidates maybe used. In other words, whether or not one of the primary transformbasis candidate and the secondary transform basis candidate is thepredetermined transform basis candidate may be whether or not the one ofthe primary transform basis candidate and the secondary transform basiscandidate is included in a plurality of predetermined transform basiscandidates.

FIG. 14 is a flowchart indicating a fourth specific example relating toprocessing for determining transform bases. FIG. 14 illustrates anoperation for determining a combination of a primary transform basis anda secondary transform basis. For example, transformer 106 of encoder 100illustrated in FIG. 1 performs the operation illustrated in FIG. 14.

More specifically, in an example of FIG. 14 as in the example of FIG.11, loop processing for each of the plurality of secondary transformbasis candidates includes loop processing for each of the plurality ofprimary transform basis candidates. Subsequently, in the loopprocessing, transformer 106 selects a primary transform basis candidateas an evaluation target primary transform basis candidate (S101), andselects a secondary transform basis candidate as an evaluation targetsecondary transform basis candidate (S102). In other words, transformer106 selects the combination of a primary transform basis candidate and asecondary transform basis candidate as the evaluation target transformbasis candidate.

In addition, as in the example of FIG. 11, transformer 106 derives acost for the combination of the primary transform basis candidate andthe secondary transform basis candidate (S103). Subsequently, in theexample of FIG. 14, transformer 106 determines whether or not a cost isless than or equal to a threshold value (S107). Here, the transform sizecorresponds to a size of a block that is transformed through one of asingle primary transform process and a single secondary transformprocess.

When the determination conditions are satisfied (Yes in S107),transformer 106 ends the loop processing. In other words, in this case,transformer 106 ends the selection processing even when a combinationthat has not been selected and evaluated is left in the plurality ofprimary transform basis candidates and the plurality of secondarytransform basis candidates. When the determination conditions are notsatisfied (No in S107), transformer 106 continues the loop processing.Here, transformer 106 repeats the processing until the determinationconditions are satisfied or no unselected combination is left.

Subsequently, transformer 106 determines the primary transform basiscandidate and the secondary transform basis candidate making up thecombination that yields the least cost out of the combinations whosecosts have been derived, as a final primary transform basis and a finalsecondary transform basis. Transformer 106 may determine the primarytransform basis candidate and the secondary transform basis candidatemaking up the combination that satisfies the determination conditions asa final primary transform basis and a final secondary transform basis.

In the example of FIG. 14, transformer 106 derives costs for a largernumber of combinations than in the example of FIG. 11. Accordingly,transformer 106 is capable of selecting a more appropriate combination.

In addition, a plurality of predetermined sizes may be used. In otherwords, whether or not the transform size is the predetermined size maybe whether or not the transform size is one of the plurality ofpredetermined sizes. In addition, the predetermined size may correspondto a size range.

For example, transformer 106 may end loop processing only when a cost isless than or equal to a threshold value and a transform size is 4×4. Inaddition, for example, transformer 106 may end loop processing only whena cost is less than or equal to a threshold value and a transform sizeis 8×8.

FIG. 15 is a flowchart indicating a fifth specific example relating toprocessing for determining transform bases. FIG. 15 illustrates anoperation for determining a combination of a primary transform basis anda secondary transform basis. For example, transformer 106 of encoder 100illustrated in FIG. 1 performs the operation illustrated in FIG. 15.

More specifically, in an example of FIG. 15 as in the example of FIG.11, loop processing for each of the plurality of secondary transformbasis candidates includes loop processing for each of the plurality ofprimary transform basis candidates. Subsequently, in the loopprocessing, transformer 106 selects a primary transform basis candidateas an evaluation target primary transform basis candidate (S101), andselects a secondary transform basis candidate as an evaluation targetsecondary transform basis candidate (S102). In other words, transformer106 selects the combination of a primary transform basis candidate and asecondary transform basis candidate as the evaluation target transformbasis candidate.

In addition, as in the example of FIG. 11, transformer 106 derives acost for the combination of the primary transform basis candidate andthe secondary transform basis candidate (S103). Subsequently, in theexample of FIG. 15, transformer 106 adaptively determines a thresholdvalue based on a coding parameter (S104). Here, coding parameter is aparameter to be coded, and may be specifically a primary transformbasis, a secondary transform basis, a block size, a quantizationparameter, or the like. For example, a threshold value when a primarytransform basis corresponds to DCT 2 and a threshold value when aprimary transform basis corresponds to DST 7 may vary.

Subsequently, transformer 106 determines whether or not a cost is lessthan or equal to a threshold value (S105), using a determined thresholdvalue.

When a cost is less than or equal to a threshold value (Yes in S105),transformer 106 ends the loop processing. In other words, in this case,transformer 106 ends the selection processing even when a combinationthat has not been selected and evaluated in the plurality of primarytransform basis candidates and the plurality of secondary transformbasis candidates. Subsequently, transformer 106 determines the primarytransform basis candidate and the secondary transform basis candidatemaking up the combination that yields the cost less than or equal to thethreshold value as a final primary transform basis and a secondarytransform basis.

When the cost is not less than or equal to the threshold value (No inS105), transformer 106 continues the loop processing. Here,subsequently, transformer 106 repeats processing until a combinationthat yields a cost less than or equal to the threshold value is selectedor no unselected combination is left. When repeating the processinguntil no unselected combination is left, transformer 106 may determinethe primary transform basis candidate and the secondary transform basiscandidate making up the combination that yields the least cost as afinal primary transform basis and a final secondary transform basis.

Through the operation, transformer 106 is capable of adaptivelydetermining the threshold value to be used to determine whether or notthe cost is less than or equal to the threshold value, based on thecoding parameter.

For example, a cost frequency distribution when a quantization parameteris 22 and a cost frequency distribution when a quantization parameter is37 may vary significantly. When the same threshold value is used inthese cases, the following events occur: a cost is highly likely toexceed the threshold value in one of the cases and a cost is highlylikely to be less than the threshold value in the other case. In theseevents, reduction in increase in the amount of processing andappropriate determination of transform bases may not be performed in abalanced manner.

In the example of FIG. 15, transformer 106 is capable of reducingincrease in the amount of processing and appropriately determiningtransform bases in a balanced manner by adaptively determining athreshold value based on a coding parameter.

The examples in FIGS. 11 to 15 may be arbitrarily combined. For example,in the examples of FIGS. 13 to 15, as in the example of FIG. 12, onlyone of loop processing for each of primary transform basis candidatesand loop processing for each of secondary transform basis candidates maybe ended.

In addition, in the examples of FIGS. 11 to 15, a threshold value for acost of a transform basis candidate may be determined as an absolutethreshold value that is independent of a cost, etc., of anothertransform basis candidate, or may be determined as a threshold valuerelative to a cost, etc., of another transform basis candidate. Inparticular, in the example of FIG. 15, the relative threshold valuedetermined by the cost of the other transform basis candidate may beadjusted by a coding parameter.

Although the examples of FIGS. 11 to 15 have been described asconfigurations in each of which transformer 106 ends both or one of theloop processing for each primary transform basis candidate and the loopprocessing for each secondary transform basis candidate whendetermination conditions are satisfied, any of the configurations may bereplaced by the following alternative configuration for continuing theloop processing by skipping only one or more particular candidates outof a plurality of primary transform basis candidates that have not beenevaluated and a plurality of secondary transform basis candidates thathave not been evaluated, instead of ending the loop processing byskipping evaluation for each of a plurality of primary transform basiscandidates that have not been evaluated and each of a plurality ofsecondary transform basis candidates that have not been evaluated.

As for the relative threshold value, for example, a threshold value maybe determined based on a representative cost before loop processing.More specifically, a cost for a combination of a primary transform basiscandidate corresponding to DCT 2 and a secondary transform basis that isnot transformed may be determined as a reference cost. A value, etc.,obtainable by multiplying the reference cost by a constant may bedetermined as a relative threshold value.

Alternatively, a cost of a representative combination of a primarytransform basis candidate and a secondary transform basis candidate maybe derived at the beginning of loop processing, and then the cost of therepresentative combination may be used as a threshold value. Forexample, a cost of a combination of a primary transform basis candidatecorresponding to DCT 2 and a secondary transform basis that is nottransformed may be derived at the beginning of loop processing.Subsequently, the cost of the combination may be used as a thresholdvalue.

Alternatively, priority ranks may be determined in advance for theplurality of combinations each composed of a primary transform basiscandidate and a secondary transform basis candidate. Subsequently,transformer 106 may select each of the combinations in a priority order(that is, in an ascending order of priority) in loop processing.Subsequently, transformer 106 may determine whether or not the cost ofeach combination is less than or equal to the cost of a previouscombination in the priority order. In other words, the cost of thecombination ranked higher than a current combination in the priorityorder may be used as a threshold value.

Here, the combination ranked higher in the priority order may be thecombination ranked directly above a current combination in the priorityorder or any of the plurality of combinations ranked higher than acurrent combination in the priority order.

In addition, in the above explanation, transformer 106 skips theselection when the cost is less than or equal to the threshold value,and does not skip the selection when the cost exceeds the thresholdvalue. However, transformer 106 may not skip selection when the cost isless than the threshold value and may skip selection when the costexceeds the threshold value.

For example, priority ranks may be determined in advance for theplurality of combinations each composed of a primary transform basiscandidate and a secondary transform basis candidate. Subsequently,transformer 106 may select each of the combinations in a priority orderin loop processing. Subsequently, when the cost of the combinationexceeds the cost of a combination ranked above, transformer 106 may endthe loop processing. In this case, the primary transform basis candidateand the secondary transform basis candidate making up the combinationranked above may be determined as a primary transform basis and asecondary transform basis.

In the above example, the threshold value is the cost of the combinationranked above. When the cost of the combination exceeds the thresholdvalue, transformer 106 skips the selection of the combination by endingthe loop processing.

Here, a cost that is desired to be less is used as an evaluation value.The evaluation value is not limited to such a cost, and may be a valuethat is desired to be larger. In addition, in each of FIGS. 11 to 15,whether or not the cost to be used as an evaluation value is less thanor equal to a threshold value is used as a determination condition.However, whether or not an evaluation value exceeds a threshold valuemay be used as a determination condition, or whether or not anevaluation value is less than a threshold value may be used as adetermination condition.

In addition, the processing for ending a loop based on a determinationresult may be validated or invalidated on a per slice basis.Alternatively, the processing for ending a loop based on a determinationresult may be validated or invalidated on a per tile basis.Alternatively, the processing for ending a loop based on a determinationresult may be validated or invalidated on a per CTU basis.Alternatively, the processing for ending a loop based on a determinationresult may be validated or invalidated on a per CU basis.

In addition, the processing for ending a loop based on a determinationresult may be validated or invalidated according to a frame type such asan I-frame, a P-frame, and a B-frame. In addition, the processing forending a loop based on a determination result may be validated orinvalidated according to a prediction mode such as intra prediction andinter prediction.

In addition, when the transform is separable into vertical transform andhorizontal transform, the processing for ending a loop based on adetermination result may be validated or invalidated independently ofthe vertical or horizontal direction. For example, processing for endinga loop based on a determination result may be performed in one of thevertical and horizontal directions, and processing for ending a loopbased on a determination result may not be performed in the other one ofthe vertical and horizontal directions. Alternatively, processing forending a loop based on a determination result may be performed in eachof the vertical and horizontal directions.

In addition, processing for ending a loop based on a determinationresult may be validated or invalidated according to one of luminance andchrominance. For example, processing for ending a loop based on adetermination result may be performed on one of luminance andchrominance, and processing for ending a loop based on a determinationresult may not be performed on the other one of luminance andchrominance. Alternatively, processing for ending a loop based on adetermination result may be performed on each of luminance andchrominance.

[Implementation Example of Encoder]

FIG. 16 is a block diagram indicating an implementation example ofencoder 100 according to Embodiment 1. Encoder 100 includes processor160 and memory 162. For example, a plurality of constituent elements ofencoder 100 illustrated in FIG. 1 are implemented as processor 160 andmemory 162 illustrated in FIG. 16.

Processor 160 is an electronic circuit accessible to memory 162, andperforms information processing. For example, processor 160 is anexclusive or general processor which codes a moving picture using memory162. Processor 160 may be a CPU.

In addition, processor 160 may be configured with a plurality ofelectronic circuits, or may be configured with a plurality ofsub-processors. In addition, processor 160 may take the roles of two ormore constituent elements other than a constituent element for storinginformation out of the plurality of constituent elements of encoder 100illustrated in FIG. 1.

Memory 162 is an exclusive or general memory for storing informationthat is used by processor 160 to code a moving picture. Memory 162 maybe an electronic circuit, may be connected to processor 160, or may beincluded in processor 160.

In addition, memory 162 may be configured with a plurality of electroniccircuits, or may be configured with a plurality of sub-memories. Inaddition, memory 162 may be a magnetic disc or an optical disc, or thelike, or may be represented as a storage, a recording medium, or thelike. In addition, memory 162 may be a non-volatile memory or a volatilememory.

For example, processor 162 may take the role of a constituent elementfor storing information out of the plurality of constituent elements ofencoder 100 illustrated in FIG. 1. More specifically, memory 162 maytake the roles of block memory 118 and frame memory 122 illustrated inFIG. 1.

In addition, memory 162 may store a moving picture to be coded or abitstream corresponding to the moving picture to be coded. In addition,memory 162 may store a program for causing processor 160 to code amoving picture. In addition, memory 162 may store, for example,information indicating a plurality of transform basis candidates.

In addition, in encoder 100, all of the plurality of constituentelements illustrated in FIG. 1 may not be implemented, and all of theprocesses described above may not be performed. Part of the constituentelements illustrated in FIG. 1 may be included in another device, orpart of the processes described above may be performed by anotherdevice. In this case, the part of the constituent elements illustratedin FIG. 1 are implemented in encoder 100, and the part of the processesdescribed above may be performed by encoder 100, which reduces increasein the amount of processing and enables appropriate determination oftransform bases.

As described above, processor 160 of encoder 100 illustrated in FIG. 16codes a moving picture using memory 162 of encoder 100.

For example, processor 160 subtracts a prediction image of an imageincluded in the moving picture from the image so as to derive aprediction error of the image. In addition, processor 160 sequentiallyselects a plurality of transform basis candidates for a transform basisto be used to perform transform of the prediction error. Subsequently,processor 160 derives an evaluation value of a transform basis candidateselected out of the plurality of transform basis candidates, andcompares the evaluation value with a threshold value.

Based on the result of the comparison, processor 160 skips selection ofone or more transform basis candidates that have not been selected outof the plurality of transform basis candidates. Subsequently, processor160 determines the transform basis from one or more transform basiscandidates selected out of the plurality of transform basis candidates.Processor 160 performs the transform of the prediction error, using thetransform basis. Subsequently, processor 160 quantizes the result of thetransform. Subsequently, processor 160 codes the result of thequantization as data of the image.

In addition, for example, the transform may include primary transformand secondary transform. In addition, the transform basis may be acombination of a primary transform basis that is a transform basis foruse in the primary transform and a secondary transform basis that is atransform basis for use in the secondary transform. In addition, each ofthe plurality of transform basis candidates may be a combination of oneof a plurality of primary transform basis candidates for the primarytransform basis and one of a plurality of secondary transform basiscandidates for the secondary transform basis.

In addition, for example, processor 160 may sequentially select theplurality of transform basis candidates by sequentially selecting theplurality of primary transform basis candidates and sequentiallyselecting the plurality of secondary transform basis candidates.

Based on the result of the comparison, processor 160 may end thesequential selection of the plurality of primary transform basiscandidates and end the sequential selection of the plurality ofsecondary transform basis candidates. In this way, processor 160 mayskip the selection of the one or more transform basis candidates thathave not been selected out of the plurality of transform basiscandidates.

In addition, for example, processor 160 may sequentially select theplurality of transform basis candidates by sequentially selecting theplurality of primary transform basis candidates and sequentiallyselecting the plurality of secondary transform basis candidates.

Based on the result of the comparison, processor 160 may skip one ofselection of one or more primary transform basis candidates that havenot been selected and selection of one or more secondary transform basiscandidates that have not been selected. In this way, processor 160 mayskip the selection of the one or more transform basis candidates thathave not been selected out of the plurality of transform basiscandidates.

In addition, for example, when the result of the comparison shows thatthe evaluation value is better than the threshold value, the processormay skip the selection of the one or more transform basis candidatesthat have not been selected. Processor 160 may the processor maydetermine the threshold value using an evaluation value of anothertransform basis candidate selected before the transform basis candidateselected. In addition, for example, processor 160 may determine thethreshold value using a parameter to be coded when coding the movingpicture.

In addition, for example, when the transform basis candidate selected isa predetermined transform basis candidate, processor 160 may skip theselection of the one or more transform basis candidates that have notbeen selected out of the plurality of transform basis candidates, basedon the result of the comparison. In addition, for example, when a sizeof the transform is a predetermined size, processor 160 may skip theselection of the one or more transform basis candidates that have notbeen selected out of the plurality of transform basis candidates, basedon the result of the comparison.

In addition, for example, processor 160 may code information indicatingthe transform basis that is determined based on the result of thecomparison.

It is to be noted that encoder 100 is not limited to the aboveimplementation example, and may include subtractor 104, transformer 106,quantizer 108, and entropy encoder 110. These constituent elements mayperform the above-described operations.

For example, subtractor 104 may subtract a prediction image of an imageincluded in the moving picture from the image so as to derive aprediction error of the image. In addition, transformer 106 maysequentially select a plurality of transform basis candidates for atransform basis to be used to perform transform of the prediction error.Subsequently, transformer 106 may derive an evaluation value of atransform basis candidate selected out of the plurality of transformbasis candidates, and compare the evaluation value with a thresholdvalue.

Based on the result of the comparison, transformer 106 may skipselection of one or more transform basis candidates that have not beenselected out of the plurality of transform basis candidates.Subsequently, transformer 106 may determine the transform basis from oneor more transform basis candidates selected out of the plurality oftransform basis candidates. Subsequently, transformer 106 may performthe transform of the prediction error, using the transform basis. Inaddition, quantizer 108 may quantize the result of the transform. Inaddition, entropy encoder 110 may code the result of the quantization asdata of the image.

Furthermore, transformer 106 may perform another operation related totransform, and entropy encoder 110 may perform another operation relatedto coding. In addition, transformer 106 may be separated into atransform base determiner which determines a primary transform basis anda secondary transform basis, a primary transformer which performsprimary transform, and a secondary transformer which performs secondarytransform.

[Implementation Example of Decoder]

FIG. 17 is a block diagram indicating an implementation example ofdecoder 200 according to Embodiment 1. Decoder 200 includes processor260 and memory 262. For example, a plurality of constituent elements ofdecoder 200 illustrated in FIG. 10 are implemented as processor 260 andmemory 262 illustrated in FIG. 17.

Processor 260 is an electronic circuit accessible to memory 262, andperforms information processing. For example, processor 260 is anexclusive or general processor which decodes a moving picture usingmemory 262. Processor 260 may be a CPU.

In addition, processor 260 may be configured with a plurality ofelectronic circuits, or may be configured with a plurality ofsub-processors. In addition, processor 260 may take the roles of two ormore constituent elements other than a constituent element for storinginformation out of the plurality of constituent elements of decoder 200illustrated in FIG. 10.

Memory 262 is an exclusive or general memory for storing informationthat is used by processor 260 to decode a moving picture. Memory 262 maybe an electronic circuit, may be connected to processor 260, or may beincluded in processor 260.

In addition, memory 262 may be configured with a plurality of electroniccircuits, or may be configured with a plurality of sub-memories. Inaddition, memory 262 may be a magnetic disc or an optical disc, or thelike, or may be represented as a storage, a recording medium, or thelike. In addition, memory 262 may be a non-volatile memory or a volatilememory.

For example, memory 262 may take the role of a constituent element forstoring information out of the plurality of constituent elements ofdecoder 200 illustrated in FIG. 10. More specifically, memory 262 maytake the roles of block memory 210 and frame memory 214 illustrated inFIG. 10.

In addition, memory 262 may store a bitstream corresponding to themoving picture coded or a moving picture corresponding to the bitstreamdecoded. In addition, memory 262 may store a program for causingprocessor 260 to decode a moving picture. In addition, memory 262 maystore, for example, information indicating a plurality of transformbasis candidates.

In addition, in decoder 200, all of the plurality of constituentelements illustrated in FIG. 10 may not be implemented, and all of theprocesses described above may not be performed. Some of the constituentelements illustrated in FIG. 10 may be included in another device, orsome of the processes described above may be performed by anotherdevice. In this case, the part of the constituent elements illustratedin FIG. 10 are implemented in decoder 200, and the part of the processesdescribed above may be performed by decoder 200, which reduces increasein the amount of processing and enables appropriate determination oftransform bases.

As described above, processor 260 of decoder 200 illustrated in FIG. 17decodes a moving picture using memory 262 of decoder 200.

For example, processor 260 decodes data of an image included in themoving picture. In addition, processor 260 decodes informationindicating a transform basis determined based on the result ofcomparison between an evaluation value of a transform basis candidateand a threshold value. In addition, processor 260 performs inversequantization of the data decoded. In addition, processor 260 performsinverse transform of the result of the inverse quantization, using thetransform basis indicated by the information decoded. In addition,processor 260 derives the image by adding, as a prediction error of theimage, the result of the inverse transform to a prediction image of theimage.

It is to be noted that decoder 200 is not limited to the above-describedimplementation, and may include entropy decoder 202, inverse quantizer204, inverse transformer 206, and adder 208. These constituent elementsmay perform the above-described operations.

For example, entropy decoder 202 may decode data of an image included inthe moving picture. In addition, entropy decoder 202 may decodeinformation indicating a transform basis determined based on the resultof comparison between an evaluation value of a transform basis candidateand a threshold value. In addition, inverse quantizer 204 may performinverse quantization of the data decoded.

In addition, inverse transformer 206 may perform inverse transform ofthe result of the inverse quantization, using the transform basisindicated by the information decoded. In addition, adder 208 may derivethe image by adding, as a prediction error of the image, the result ofthe inverse transform to a prediction image of the image.

Furthermore, inverse transformer 206 may perform other operationsrelated to the transform, or entropy decoder 202 may perform otheroperations related to the decoding. In addition, inverse transformer 206may be separated into a transform basis determiner which determines aninverse primary transform basis and an inverse secondary transformbasis, an inverse primary transformer which transforms inverse primarytransform, and an inverse secondary transformer which transforms inversesecondary transform.

[Supplement]

Encoder 100 and decoder 200 according to this embodiment may be used asan image encoder and an image decoder, or may be used as a movingpicture encoder and a moving picture decoder. Alternatively, each ofencoder 100 and decoder 200 can be used as a transformer.

In other words, each of encoder 100 and decoder 200 may correspond toonly one of transformer 106 and inverse transformer 206. Subsequently,inter predictors 126 and 218 and other constituent elements may beincluded in other devices.

In addition, at least part of this embodiment may be used as a codingmethod, a decoding method, a transforming method, or other methods.

In addition, in this embodiment, each of the constituent elements may beconfigured with exclusive hardware, or may be implemented by executing asoftware program suitable for each constituent element. Each constituentelement may be implemented by means of a program executer such as a CPUand a processor reading and executing a software program stored in arecording medium such as a hard disc or a semiconductor memory.

More specifically, each of encoder 100 and decoder 200 may includeprocessing circuitry and storage electrically connected to theprocessing circuitry and accessible from the processing circuitry. Forexample, the processing circuitry corresponds to one of processors 160and 260, and the storage corresponds to one of memories 162 and 262.

The processing circuitry includes at least one of the exclusive hardwareand the program executer. In addition, when the processing circuitryincludes the program executer, the storage stores a software programthat is executed by the program executer.

Here, the software which implements encoder 100, decoder 200, etc.,according to this embodiment includes programs as indicated below.

In other words, the program may cause a computer to execute such acoding method for coding a moving picture that includes: subtracting aprediction image of an image included in the moving picture from theimage so as to derive a prediction error of the image; sequentiallyselecting a plurality of transform basis candidates for a transformbasis to be used to perform transform of the prediction error; derivingan evaluation value of a transform basis candidate selected out of theplurality of transform basis candidates; comparing the evaluation valuewith a threshold value; based on the result of the comparison, skippingselection of one or more transform basis candidates that have not beenselected out of the plurality of transform basis candidates; determiningthe transform basis from one or more transform basis candidates selectedout of the plurality of transform basis candidates; performing thetransform of the prediction error, using the transform basis; quantizingthe result of the transform; and coding the result of the quantizationas data of the image.

Alternatively, the program may cause such a decoding method for decodinga moving picture that includes: decoding data of an image included inthe moving picture; decoding information indicating a transform basisdetermined based on the result of comparison between an evaluation valueof a transform basis candidate and a threshold value; performing inversequantization of the data decoded; performing inverse transform of theresult of the inverse quantization, using the transform basis indicatedby the information decoded; and deriving the image by adding, as aprediction error of the image, the result of the inverse transform to aprediction image of the image.

In addition, each constituent element may be circuitry as describedabove. Circuits may compose circuitry as a whole, or may be separatecircuits. Alternatively, each constituent element may be implemented asa general processor, or may be implemented as an exclusive processor.

In addition, the processing that is executed by a particular constituentelement may be executed by another constituent element. In addition, theprocessing execution order may be modified, or a plurality of processesmay be executed in parallel. In addition, an encoder and decoder mayinclude encoder 100 and decoder 200.

In addition, the ordinal numbers such as “first” and “second” used forexplanation may be arbitrarily changed. A new ordinal number may beattached to a constituent element, or an ordinal number attached to aconstituent element may be removed.

Although some aspects of encoder 100 and decoder 200 have been explainedbased on the above embodiments, aspects of encoder 100 and decoder 200are not limited to these embodiments. The scope of the aspects ofencoder 100 and decoder 200 may encompasses embodiments obtainable byadding, to any of these embodiments, various kinds of modifications thata person skilled in the art would arrive at without deviating from thescope of the present disclosure and embodiments configurable byarbitrarily combining constituent elements in different embodiments.

One of the aspects may be performed by combining at least part of theother aspects in the present disclosure. In addition, one of the aspectsmay be performed by combining part of the processing indicated in any ofthe flowcharts according to one of the aspects, part of theconfiguration of any of the devices, part of syntaxes, etc.

Embodiment 2

As described in each of the above embodiments, each functional block cantypically be realized as an MPU and memory, for example. Moreover,processes performed by each of the functional blocks are typicallyrealized by a program execution unit, such as a processor, reading andexecuting software (a program) recorded on a recording medium such asROM. The software may be distributed via, for example, downloading, andmay be recorded on a recording medium such as semiconductor memory anddistributed. Note that each functional block can, of course, also berealized as hardware (dedicated circuit).

Moreover, the processing described in each of the embodiments may berealized via integrated processing using a single apparatus (system),and, alternatively, may be realized via decentralized processing using aplurality of apparatuses. Moreover, the processor that executes theabove-described program may be a single processor or a plurality ofprocessors. In other words, integrated processing may be performed, and,alternatively, decentralized processing may be performed.

Embodiments of the present disclosure are not limited to the aboveexemplary embodiments; various modifications may be made to theexemplary embodiments, the results of which are also included within thescope of the embodiments of the present disclosure.

Next, application examples of the moving picture encoding method (imageencoding method) and the moving picture decoding method (image decodingmethod) described in each of the above embodiments and a system thatemploys the same will be described. The system is characterized asincluding an image encoding device that employs the image encodingmethod, an image decoding device that employs the image decoding method,and an image encoding/decoding device that includes both the imageencoding device and the image decoding device. Other configurationsincluded in the system may be modified on a case-by-case basis.

[Usage Examples]

FIG. 18 illustrates an overall configuration of content providing systemex100 for implementing a content distribution service. The area in whichthe communication service is provided is divided into cells of desiredsizes, and base stations ex106, ex107, ex108, ex109, and ex110, whichare fixed wireless stations, are located in respective cells.

In content providing system ex100, devices including computer ex111,gaming device ex112, camera ex113, home appliance ex114, and smartphoneex115 are connected to internet ex101 via internet service providerex102 or communications network ex104 and base stations ex106 throughex110. Content providing system ex100 may combine and connect anycombination of the above elements. The devices may be directly orindirectly connected together via a telephone network or near fieldcommunication rather than via base stations ex106 through ex110, whichare fixed wireless stations. Moreover, streaming server ex103 isconnected to devices including computer ex111, gaming device ex112,camera ex113, home appliance ex114, and smartphone ex115 via, forexample, internet ex101. Streaming server ex103 is also connected to,for example, a terminal in a hotspot in airplane ex117 via satelliteex116.

Note that instead of base stations ex106 through ex110, wireless accesspoints or hotspots may be used. Streaming server ex103 may be connectedto communications network ex104 directly instead of via internet ex101or internet service provider ex102, and may be connected to airplaneex117 directly instead of via satellite ex116.

Camera ex113 is a device capable of capturing still images and video,such as a digital camera. Smartphone ex115 is a smartphone device,cellular phone, or personal handyphone system (PHS) phone that canoperate under the mobile communications system standards of the typical2G, 3G, 3.9G, and 4G systems, as well as the next-generation 5G system.

Home appliance ex118 is, for example, a refrigerator or a deviceincluded in a home fuel cell cogeneration system.

In content providing system ex100, a terminal including an image and/orvideo capturing function is capable of, for example, live streaming byconnecting to streaming server ex103 via, for example, base stationex106. When live streaming, a terminal (e.g., computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, orairplane ex117) performs the encoding processing described in the aboveembodiments on still-image or video content captured by a user via theterminal, multiplexes video data obtained via the encoding and audiodata obtained by encoding audio corresponding to the video, andtransmits the obtained data to streaming server ex103. In other words,the terminal functions as the image encoding device according to oneaspect of the present disclosure.

Streaming server ex103 streams transmitted content data to clients thatrequest the stream. Client examples include computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, andterminals inside airplane ex117, which are capable of decoding theabove-described encoded data. Devices that receive the streamed datadecode and reproduce the received data. In other words, the devices eachfunction as the image decoding device according to one aspect of thepresent disclosure.

[Decentralized Processing]

Streaming server ex103 may be realized as a plurality of servers orcomputers between which tasks such as the processing, recording, andstreaming of data are divided. For example, streaming server ex103 maybe realized as a content delivery network (CDN) that streams content viaa network connecting multiple edge servers located throughout the world.In a CDN, an edge server physically near the client is dynamicallyassigned to the client. Content is cached and streamed to the edgeserver to reduce load times. In the event of, for example, some kind ofan error or a change in connectivity due to, for example, a spike intraffic, it is possible to stream data stably at high speeds since it ispossible to avoid affected parts of the network by, for example,dividing the processing between a plurality of edge servers or switchingthe streaming duties to a different edge server, and continuingstreaming.

Decentralization is not limited to just the division of processing forstreaming; the encoding of the captured data may be divided between andperformed by the terminals, on the server side, or both. In one example,in typical encoding, the processing is performed in two loops. The firstloop is for detecting how complicated the image is on a frame-by-frameor scene-by-scene basis, or detecting the encoding load. The second loopis for processing that maintains image quality and improves encodingefficiency. For example, it is possible to reduce the processing load ofthe terminals and improve the quality and encoding efficiency of thecontent by having the terminals perform the first loop of the encodingand having the server side that received the content perform the secondloop of the encoding. In such a case, upon receipt of a decodingrequest, it is possible for the encoded data resulting from the firstloop performed by one terminal to be received and reproduced on anotherterminal in approximately real time. This makes it possible to realizesmooth, real-time streaming.

In another example, camera ex113 or the like extracts a feature amountfrom an image, compresses data related to the feature amount asmetadata, and transmits the compressed metadata to a server. Forexample, the server determines the significance of an object based onthe feature amount and changes the quantization accuracy accordingly toperform compression suitable for the meaning of the image. Featureamount data is particularly effective in improving the precision andefficiency of motion vector prediction during the second compressionpass performed by the server. Moreover, encoding that has a relativelylow processing load, such as variable length coding (VLC), may behandled by the terminal, and encoding that has a relatively highprocessing load, such as context-adaptive binary arithmetic coding(CABAC), may be handled by the server.

In yet another example, there are instances in which a plurality ofvideos of approximately the same scene are captured by a plurality ofterminals in, for example, a stadium, shopping mall, or factory. In sucha case, for example, the encoding may be decentralized by dividingprocessing tasks between the plurality of terminals that captured thevideos and, if necessary, other terminals that did not capture thevideos and the server, on a per-unit basis. The units may be, forexample, groups of pictures (GOP), pictures, or tiles resulting fromdividing a picture. This makes it possible to reduce load times andachieve streaming that is closer to real-time.

Moreover, since the videos are of approximately the same scene,management and/or instruction may be carried out by the server so thatthe videos captured by the terminals can be cross-referenced. Moreover,the server may receive encoded data from the terminals, change referencerelationship between items of data or correct or replace picturesthemselves, and then perform the encoding. This makes it possible togenerate a stream with increased quality and efficiency for theindividual items of data.

Moreover, the server may stream video data after performing transcodingto convert the encoding format of the video data. For example, theserver may convert the encoding format from MPEG to VP, and may convertH.264 to H.265.

In this way, encoding can be performed by a terminal or one or moreservers. Accordingly, although the device that performs the encoding isreferred to as a “server” or “terminal” in the following description,some or all of the processes performed by the server may be performed bythe terminal, and likewise some or all of the processes performed by theterminal may be performed by the server. This also applies to decodingprocesses.

[3D, Multi-Angle]

In recent years, usage of images or videos combined from images orvideos of different scenes concurrently captured or the same scenecaptured from different angles by a plurality of terminals such ascamera ex113 and/or smartphone ex115 has increased. Videos captured bythe terminals are combined based on, for example, theseparately-obtained relative positional relationship between theterminals, or regions in a video having matching feature points.

In addition to the encoding of two-dimensional moving pictures, theserver may encode a still image based on scene analysis of a movingpicture either automatically or at a point in time specified by theuser, and transmit the encoded still image to a reception terminal.Furthermore, when the server can obtain the relative positionalrelationship between the video capturing terminals, in addition totwo-dimensional moving pictures, the server can generatethree-dimensional geometry of a scene based on video of the same scenecaptured from different angles. Note that the server may separatelyencode three-dimensional data generated from, for example, a pointcloud, and may, based on a result of recognizing or tracking a person orobject using three-dimensional data, select or reconstruct and generatea video to be transmitted to a reception terminal from videos capturedby a plurality of terminals.

This allows the user to enjoy a scene by freely selecting videoscorresponding to the video capturing terminals, and allows the user toenjoy the content obtained by extracting, from three-dimensional datareconstructed from a plurality of images or videos, a video from aselected viewpoint. Furthermore, similar to with video, sound may berecorded from relatively different angles, and the server may multiplex,with the video, audio from a specific angle or space in accordance withthe video, and transmit the result.

In recent years, content that is a composite of the real world and avirtual world, such as virtual reality (VR) and augmented reality (AR)content, has also become popular. In the case of VR images, the servermay create images from the viewpoints of both the left and right eyesand perform encoding that tolerates reference between the two viewpointimages, such as multi-view coding (MVC), and, alternatively, may encodethe images as separate streams without referencing. When the images aredecoded as separate streams, the streams may be synchronized whenreproduced so as to recreate a virtual three-dimensional space inaccordance with the viewpoint of the user.

In the case of AR images, the server superimposes virtual objectinformation existing in a virtual space onto camera informationrepresenting a real-world space, based on a three-dimensional positionor movement from the perspective of the user. The decoding device mayobtain or store virtual object information and three-dimensional data,generate two-dimensional images based on movement from the perspectiveof the user, and then generate superimposed data by seamlesslyconnecting the images. Alternatively, the decoding device may transmit,to the server, motion from the perspective of the user in addition to arequest for virtual object information, and the server may generatesuperimposed data based on three-dimensional data stored in the serverin accordance with the received motion, and encode and stream thegenerated superimposed data to the decoding device. Note thatsuperimposed data includes, in addition to RGB values, an a valueindicating transparency, and the server sets the a value for sectionsother than the object generated from three-dimensional data to, forexample, 0, and may perform the encoding while those sections aretransparent. Alternatively, the server may set the background to apredetermined RGB value, such as a chroma key, and generate data inwhich areas other than the object are set as the background.

Decoding of similarly streamed data may be performed by the client(i.e., the terminals), on the server side, or divided therebetween. Inone example, one terminal may transmit a reception request to a server,the requested content may be received and decoded by another terminal,and a decoded signal may be transmitted to a device having a display. Itis possible to reproduce high image quality data by decentralizingprocessing and appropriately selecting content regardless of theprocessing ability of the communications terminal itself. In yet anotherexample, while a TV, for example, is receiving image data that is largein size, a region of a picture, such as a tile obtained by dividing thepicture, may be decoded and displayed on a personal terminal orterminals of a viewer or viewers of the TV. This makes it possible forthe viewers to share a big-picture view as well as for each viewer tocheck his or her assigned area or inspect a region in further detail upclose.

In the future, both indoors and outdoors, in situations in which aplurality of wireless connections are possible over near, mid, and fardistances, it is expected to be able to seamlessly receive content evenwhen switching to data appropriate for the current connection, using astreaming system standard such as MPEG-DASH. With this, the user canswitch between data in real time while freely selecting a decodingdevice or display apparatus including not only his or her own terminal,but also, for example, displays disposed indoors or outdoors. Moreover,based on, for example, information on the position of the user, decodingcan be performed while switching which terminal handles decoding andwhich terminal handles the displaying of content. This makes it possibleto, while in route to a destination, display, on the wall of a nearbybuilding in which a device capable of displaying content is embedded oron part of the ground, map information while on the move. Moreover, itis also possible to switch the bit rate of the received data based onthe accessibility to the encoded data on a network, such as when encodeddata is cached on a server quickly accessible from the receptionterminal or when encoded data is copied to an edge server in a contentdelivery service.

[Scalable Encoding]

The switching of content will be described with reference to a scalablestream, illustrated in FIG. 19, that is compression coded viaimplementation of the moving picture encoding method described in theabove embodiments. The server may have a configuration in which contentis switched while making use of the temporal and/or spatial scalabilityof a stream, which is achieved by division into and encoding of layers,as illustrated in FIG. 19. Note that there may be a plurality ofindividual streams that are of the same content but different quality.In other words, by determining which layer to decode up to based oninternal factors, such as the processing ability on the decoding deviceside, and external factors, such as communication bandwidth, thedecoding device side can freely switch between low resolution contentand high resolution content while decoding. For example, in a case inwhich the user wants to continue watching, at home on a device such as aTV connected to the internet, a video that he or she had been previouslywatching on smartphone ex115 while on the move, the device can simplydecode the same stream up to a different layer, which reduces serverside load.

Furthermore, in addition to the configuration described above in whichscalability is achieved as a result of the pictures being encoded perlayer and the enhancement layer is above the base layer, the enhancementlayer may include metadata based on, for example, statisticalinformation on the image, and the decoding device side may generate highimage quality content by performing super-resolution imaging on apicture in the base layer based on the metadata. Super-resolutionimaging may be improving the SN ratio while maintaining resolutionand/or increasing resolution. Metadata includes information foridentifying a linear or a non-linear filter coefficient used insuper-resolution processing, or information identifying a parametervalue in filter processing, machine learning, or least squares methodused in super-resolution processing.

Alternatively, a configuration in which a picture is divided into, forexample, tiles in accordance with the meaning of, for example, an objectin the image, and on the decoding device side, only a partial region isdecoded by selecting a tile to decode, is also acceptable. Moreover, bystoring an attribute about the object (person, car, ball, etc.) and aposition of the object in the video (coordinates in identical images) asmetadata, the decoding device side can identify the position of adesired object based on the metadata and determine which tile or tilesinclude that object. For example, as illustrated in FIG. 20, metadata isstored using a data storage structure different from pixel data such asan SEI message in HEVC. This metadata indicates, for example, theposition, size, or color of the main object.

Moreover, metadata may be stored in units of a plurality of pictures,such as stream, sequence, or random access units. With this, thedecoding device side can obtain, for example, the time at which aspecific person appears in the video, and by fitting that with pictureunit information, can identify a picture in which the object is presentand the position of the object in the picture.

[Web Page Optimization]

FIG. 21 illustrates an example of a display screen of a web page on, forexample, computer ex111. FIG. 22 illustrates an example of a displayscreen of a web page on, for example, smartphone ex115. As illustratedin FIG. 21 and FIG. 22, a web page may include a plurality of imagelinks which are links to image content, and the appearance of the webpage differs depending on the device used to view the web page. When aplurality of image links are viewable on the screen, until the userexplicitly selects an image link, or until the image link is in theapproximate center of the screen or the entire image link fits in thescreen, the display apparatus (decoding device) displays, as the imagelinks, still images included in the content or I pictures, displaysvideo such as an animated gif using a plurality of still images or Ipictures, for example, or receives only the base layer and decodes anddisplays the video.

When an image link is selected by the user, the display apparatusdecodes giving the highest priority to the base layer. Note that ifthere is information in the HTML code of the web page indicating thatthe content is scalable, the display apparatus may decode up to theenhancement layer. Moreover, in order to guarantee real timereproduction, before a selection is made or when the bandwidth isseverely limited, the display apparatus can reduce delay between thepoint in time at which the leading picture is decoded and the point intime at which the decoded picture is displayed (that is, the delaybetween the start of the decoding of the content to the displaying ofthe content) by decoding and displaying only forward reference pictures(I picture, P picture, forward reference B picture). Moreover, thedisplay apparatus may purposely ignore the reference relationshipbetween pictures and coarsely decode all B and P pictures as forwardreference pictures, and then perform normal decoding as the number ofpictures received over time increases.

[Autonomous Driving]

When transmitting and receiving still image or video data such two- orthree-dimensional map information for autonomous driving or assisteddriving of an automobile, the reception terminal may receive, inaddition to image data belonging to one or more layers, information on,for example, the weather or road construction as metadata, and associatethe metadata with the image data upon decoding. Note that metadata maybe assigned per layer and, alternatively, may simply be multiplexed withthe image data.

In such a case, since the automobile, drone, airplane, etc., includingthe reception terminal is mobile, the reception terminal can seamlesslyreceive and decode while switching between base stations among basestations ex106 through ex110 by transmitting information indicating theposition of the reception terminal upon reception request. Moreover, inaccordance with the selection made by the user, the situation of theuser, or the bandwidth of the connection, the reception terminal candynamically select to what extent the metadata is received or to whatextent the map information, for example, is updated.

With this, in content providing system ex100, the client can receive,decode, and reproduce, in real time, encoded information transmitted bythe user.

[Streaming of Individual Content]

In content providing system ex100, in addition to high image quality,long content distributed by a video distribution entity, unicast ormulticast streaming of low image quality, short content from anindividual is also possible. Moreover, such content from individuals islikely to further increase in popularity. The server may first performediting processing on the content before the encoding processing inorder to refine the individual content. This may be achieved with, forexample, the following configuration.

In real-time while capturing video or image content or after the contenthas been captured and accumulated, the server performs recognitionprocessing based on the raw or encoded data, such as capture errorprocessing, scene search processing, meaning analysis, and/or objectdetection processing. Then, based on the result of the recognitionprocessing, the server—either when prompted or automatically—edits thecontent, examples of which include: correction such as focus and/ormotion blur correction; removing low-priority scenes such as scenes thatare low in brightness compared to other pictures or out of focus; objectedge adjustment; and color tone adjustment. The server encodes theedited data based on the result of the editing. It is known thatexcessively long videos tend to receive fewer views. Accordingly, inorder to keep the content within a specific length that scales with thelength of the original video, the server may, in addition to thelow-priority scenes described above, automatically clip out scenes withlow movement based on an image processing result. Alternatively, theserver may generate and encode a video digest based on a result of ananalysis of the meaning of a scene.

Note that there are instances in which individual content may includecontent that infringes a copyright, moral right, portrait rights, etc.Such an instance may lead to an unfavorable situation for the creator,such as when content is shared beyond the scope intended by the creator.Accordingly, before encoding, the server may, for example, edit imagesso as to blur faces of people in the periphery of the screen or blur theinside of a house, for example. Moreover, the server may be configuredto recognize the faces of people other than a registered person inimages to be encoded, and when such faces appear in an image, forexample, apply a mosaic filter to the face of the person. Alternatively,as pre- or post-processing for encoding, the user may specify, forcopyright reasons, a region of an image including a person or a regionof the background be processed, and the server may process the specifiedregion by, for example, replacing the region with a different image orblurring the region. If the region includes a person, the person may betracked in the moving picture the head region may be replaced withanother image as the person moves.

Moreover, since there is a demand for real-time viewing of contentproduced by individuals, which tends to be small in data size, thedecoding device first receives the base layer as the highest priorityand performs decoding and reproduction, although this may differdepending on bandwidth. When the content is reproduced two or moretimes, such as when the decoding device receives the enhancement layerduring decoding and reproduction of the base layer and loops thereproduction, the decoding device may reproduce a high image qualityvideo including the enhancement layer. If the stream is encoded usingsuch scalable encoding, the video may be low quality when in anunselected state or at the start of the video, but it can offer anexperience in which the image quality of the stream progressivelyincreases in an intelligent manner. This is not limited to just scalableencoding; the same experience can be offered by configuring a singlestream from a low quality stream reproduced for the first time and asecond stream encoded using the first stream as a reference.

[Other Usage Examples]

The encoding and decoding may be performed by LSI ex500, which istypically included in each terminal. LSI ex500 may be configured of asingle chip or a plurality of chips. Software for encoding and decodingmoving pictures may be integrated into some type of a recording medium(such as a CD-ROM, a flexible disk, or a hard disk) that is readable by,for example, computer ex111, and the encoding and decoding may beperformed using the software. Furthermore, when smartphone ex115 isequipped with a camera, the video data obtained by the camera may betransmitted. In this case, the video data is coded by LSI ex500 includedin smartphone ex115.

Note that LSI ex500 may be configured to download and activate anapplication. In such a case, the terminal first determines whether it iscompatible with the scheme used to encode the content or whether it iscapable of executing a specific service. When the terminal is notcompatible with the encoding scheme of the content or when the terminalis not capable of executing a specific service, the terminal firstdownloads a codec or application software then obtains and reproducesthe content.

Aside from the example of content providing system ex100 that usesinternet ex101, at least the moving picture encoding device (imageencoding device) or the moving picture decoding device (image decodingdevice) described in the above embodiments may be implemented in adigital broadcasting system. The same encoding processing and decodingprocessing may be applied to transmit and receive broadcast radio wavessuperimposed with multiplexed audio and video data using, for example, asatellite, even though this is geared toward multicast whereas unicastis easier with content providing system ex100.

[Hardware Configuration]

FIG. 23 illustrates smartphone ex115. FIG. 24 illustrates aconfiguration example of smartphone ex115. Smartphone ex115 includesantenna ex450 for transmitting and receiving radio waves to and frombase station ex110, camera ex465 capable of capturing video and stillimages, and display ex458 that displays decoded data, such as videocaptured by camera ex465 and video received by antenna ex450. Smartphoneex115 further includes user interface ex466 such as a touch panel, audiooutput unit ex457 such as a speaker for outputting speech or otheraudio, audio input unit ex456 such as a microphone for audio input,memory ex467 capable of storing decoded data such as captured video orstill images, recorded audio, received video or still images, and mail,as well as decoded data, and slot ex464 which is an interface for SIMex468 for authorizing access to a network and various data. Note thatexternal memory may be used instead of memory ex467.

Moreover, main controller ex460 which comprehensively controls displayex458 and user interface ex466, power supply circuit ex461, userinterface input controller ex462, video signal processor ex455, camerainterface ex463, display controller ex459, modulator/demodulator ex452,multiplexer/demultiplexer ex453, audio signal processor ex454, slotex464, and memory ex467 are connected via bus ex470.

When the user turns the power button of power supply circuit ex461 on,smartphone ex115 is powered on into an operable state by each componentbeing supplied with power from a battery pack.

Smartphone ex115 performs processing for, for example, calling and datatransmission, based on control performed by main controller ex460, whichincludes a CPU, ROM, and RAM. When making calls, an audio signalrecorded by audio input unit ex456 is converted into a digital audiosignal by audio signal processor ex454, and this is applied with spreadspectrum processing by modulator/demodulator ex452 and digital-analogconversion and frequency conversion processing by transmitter/receiverex451, and then transmitted via antenna ex450. The received data isamplified, frequency converted, and analog-digital converted, inversespread spectrum processed by modulator/demodulator ex452, converted intoan analog audio signal by audio signal processor ex454, and then outputfrom audio output unit ex457. In data transmission mode, text,still-image, or video data is transmitted by main controller ex460 viauser interface input controller ex462 as a result of operation of, forexample, user interface ex466 of the main body, and similar transmissionand reception processing is performed. In data transmission mode, whensending a video, still image, or video and audio, video signal processorex455 compression encodes, via the moving picture encoding methoddescribed in the above embodiments, a video signal stored in memoryex467 or a video signal input from camera ex465, and transmits theencoded video data to multiplexer/demultiplexer ex453. Moreover, audiosignal processor ex454 encodes an audio signal recorded by audio inputunit ex456 while camera ex465 is capturing, for example, a video orstill image, and transmits the encoded audio data tomultiplexer/demultiplexer ex453. Multiplexer/demultiplexer ex453multiplexes the encoded video data and encoded audio data using apredetermined scheme, modulates and converts the data usingmodulator/demodulator (modulator/demodulator circuit) ex452 andtransmitter/receiver ex451, and transmits the result via antenna ex450.

When video appended in an email or a chat, or a video linked from a webpage, for example, is received, in order to decode the multiplexed datareceived via antenna ex450, multiplexer/demultiplexer ex453demultiplexes the multiplexed data to divide the multiplexed data into abitstream of video data and a bitstream of audio data, supplies theencoded video data to video signal processor ex455 via synchronous busex470, and supplies the encoded audio data to audio signal processorex454 via synchronous bus ex470. Video signal processor ex455 decodesthe video signal using a moving picture decoding method corresponding tothe moving picture encoding method described in the above embodiments,and video or a still image included in the linked moving picture file isdisplayed on display ex458 via display controller ex459. Moreover, audiosignal processor ex454 decodes the audio signal and outputs audio fromaudio output unit ex457. Note that since real-time streaming is becomingmore and more popular, there are instances in which reproduction of theaudio may be socially inappropriate depending on the user's environment.Accordingly, as an initial value, a configuration in which only videodata is reproduced, i.e., the audio signal is not reproduced, ispreferable. Audio may be synchronized and reproduced only when an input,such as when the user clicks video data, is received.

Although smartphone ex115 was used in the above example, threeimplementations are conceivable: a transceiver terminal including bothan encoding device and a decoding device; a transmitter terminalincluding only an encoding device; and a receiver terminal includingonly a decoding device. Further, in the description of the digitalbroadcasting system, an example is given in which multiplexed dataobtained as a result of video data being multiplexed with, for example,audio data, is received or transmitted, but the multiplexed data may bevideo data multiplexed with data other than audio data, such as textdata related to the video. Moreover, the video data itself rather thanmultiplexed data maybe received or transmitted.

Although main controller ex460 including a CPU is described ascontrolling the encoding or decoding processes, terminals often includeGPUs. Accordingly, a configuration is acceptable in which a large areais processed at once by making use of the performance ability of the GPUvia memory shared by the CPU and GPU or memory including an address thatis managed so as to allow common usage by the CPU and GPU. This makes itpossible to shorten encoding time, maintain the real-time nature of thestream, and reduce delay. In particular, processing relating to motionestimation, deblocking filtering, sample adaptive offset (SAO), andtransformation/quantization can be effectively carried out by the GPUinstead of the CPU in units of, for example pictures, all at once.

INDUSTRIAL APPLICABILITY

The present disclosure is applicable to, for example, televisionreceivers, digital video recorders, car navigation systems, mobilephones, digital cameras, digital video cameras, teleconferencingsystems, electronic mirrors, etc.

1-13. (canceled)
 14. A decoder comprising: a processor; and a memory,wherein the processor, using the memory: inverse quantizes datacorresponding to a current block of an image; performs an inversesecondary transform, using one candidate of the inverse secondarytransform selected from candidates of the inverse secondary transform,on a result of the inverse quantization to generate second transformcoefficients, the candidates of the inverse secondary transformincluding transform bases for the inverse secondary transform and a skipof the inverse secondary transform; and performs an inverse primarytransform, using one candidate of the inverse primary transform selectedfrom candidates of the inverse primary transform, on the secondtransform coefficients or the result of the inverse quantization togenerate first transform coefficients, the candidates of the inverseprimary transform including transform bases for the inverse primarytransform, wherein when a selected candidate of the inverse primarytransform is other than a first candidate, a fixedly selected secondcandidate is used for the inverse secondary transform, and when theselected candidate of the inverse secondary transform is other than thesecond candidate, the fixedly selected first candidate is used for theinverse primary transform.
 15. A decoding method comprising: performinginverse quantization of data corresponding to a current block of animage; performing an inverse secondary transform, using one candidate ofthe inverse secondary transform selected from candidates of the inversesecondary transform, on a result of the inverse quantization to generatesecond transform coefficients, the candidates of the inverse secondarytransform including transform bases for the inverse secondary transformand a skip of the inverse secondary transform; and performing an inverseprimary transform, using one candidate of the inverse primary transformselected from candidates of the inverse primary transform, on the secondtransform coefficients or the result of the inverse quantization togenerate first transform coefficients, the candidates of the inverseprimary transform including transform bases for the inverse primarytransform, wherein when a selected candidate of the inverse primarytransform is other than a first candidate, a fixedly selected secondcandidate is used for the inverse secondary transform; and when theselected candidate of the inverse secondary transform is other than thesecond candidate, the fixedly selected first candidate is used for theinverse primary transform.
 16. An encoder comprising: a processor; and amemory, wherein the processor, using the memory: performs a primarytransform, using one candidate of the primary transform selected fromcandidates of the primary transform, on residual signals of a currentblock to generate first transform coefficients, the candidates of theprimary transform including transform bases for the primary transform;performs a secondary transform, using one candidate of the secondarytransform selected from candidates of the secondary transform, on thefirst transform coefficients to generate second transform coefficients,the candidates of the secondary transform including transform bases forthe secondary transform and a skip of the secondary transform; andquantizes the first transform coefficients or the second transformcoefficients to generate quantized coefficients, wherein when a selectedcandidate of the primary transform is other than a first candidate, afixedly selected second candidate is used for the secondary transform,when the selected candidate of the secondary transform is other than thesecond candidate, the fixedly selected first candidate is used for theprimary transform, and the residual signals are luma signals.
 17. Anon-transitory computer readable medium storing a bitstream, thebitstream comprising: information according to which a decoder selects askip of an inverse secondary transform from candidates of inversesecondary transform; and a picture including a current block on which adecoding process is performed, wherein in the decoding process: inversequantization is performed on data corresponding to the current block ofan image; an inverse secondary transform is performed, using onecandidate of the inverse secondary transform selected from thecandidates of the inverse secondary transform, on a result of theinverse quantization to generate second transform coefficients, thecandidates of the inverse secondary transform including transform basesfor the inverse secondary transform and the skip of the inversesecondary transform; and an inverse primary transform is performed,using one candidate of the inverse primary transform selected fromcandidates of the inverse primary transform, on the second transformcoefficients or the result of the inverse quantization to generate firsttransform coefficients, the candidates of the inverse primary transformincluding transform bases for the inverse primary transform, when aselected candidate of the inverse primary transform is other than afirst candidate, a fixedly selected second candidate is used for theinverse secondary transform, and when the selected candidate of theinverse secondary transform is other than the second candidate, thefixedly selected first candidate is used for the inverse primarytransform.